Masters Degrees (Ai)

Learn how to create artificial information systems that mimic biological systems as well as how to use theoretical insights from AI to better understand cognitive processing in humans.
The human brain is a hugely complex machine that is able to perform tasks that are vastly beyond current capabilities of artificial systems. Understanding the brain has always been a source of inspiration for developing artificially intelligent agents and has led to some of the defining moments in the history of AI. At the same time, theoretical insights from artificial intelligence provide new ways to understand and probe neural information processing in biological systems.
On the one hand, the Master’s in Computation in Neural and Artificial Systems addresses how models based on neural information processing can be used to develop artificial systems, probing of human information processing in closed-loop online settings, as well as the development of new machine learning techniques to better understand human brain function.
On the other hand it addresses various ways of modelling and understanding cognitive processing in humans. These range from abstract mathematical models of learning that are derived from Bayesian statistics, complexity theory and optimal control theory to neural information processing systems such as neural networks that simulate particular cognitive functions in a biologically inspired manner. We also look at new groundbreaking areas in the field of AI, like brain computer interfacing and deep learning.

See the website http://www.ru.nl/masters/ai/computation

Why study Computation in Neural and Artificial Systems at Radboud University?
- Our cognitive focus leads to a highly interdisciplinary AI programme where students gain skills and knowledge from a number of different areas such as mathematics, computer science, psychology and neuroscience combined with a core foundation of artificial intelligence.

- Together with the world-renowned Donders Institute, the Behavioural Science Institute and various other leading research centres in Nijmegen, we train our students to become excellent researchers in AI.

- Master’s students are free to use the state-of-the-art facilities available on campus, like equipment for brain imaging as EEG, fMRI and MEG.

- Exceptional students who choose this specialisation have the opportunity to study for a double degree in Artificial Intelligence together with the specialisation in Brain Network and Neuronal Communication. This will take three instead of two years.

- This specialisation offers plenty of room to create a programme that meets your own academic and professional interests.

- To help you decide on a research topic there is a semi-annual Thesis Fair where academics and companies present possible project ideas. Often there are more project proposals than students to accept them, giving you ample choice. We are also open to any of you own ideas for research.

- Our AI students are a close-knit group; they have their own room in which they often get together to interact, debate and develop their ideas. Every student also receives personal guidance and supervision from a member of our expert staff.

Our research in this field

The programme is closely related to the research carried out in the internationally renowned Donders Institute for Brain, Cognition and Behaviour. This institute has several unique facilities for brain imaging using EEG, fMRI and MEG. You will be able to use these facilities for developing new experimental research techniques, as well as for developing new machine learning algorithms to analyse the brain data and integrate them with brain-computer interfacing systems.

Some examples of possible thesis subjects:
- Deep learning
Recent breakthroughs in AI have led to the development of artificial neural networks that achieve human level performance in object recognition. This has led companies like Google and Facebook to invest a lot of research in this technology. Within the AI department you can do research on this topic. This can range from developing deep neural networks to map and decode thoughts from human brain activity to the development of speech recognition systems or neural networks that can play arcade games.

- Brain Computer Interfacing
Brain computer interfaces are systems which decode a users mental state online in real-time for the purpose of communication or control. An effective BCI requires both neuro-scientific insight (which mental states should we decode?) and technical expertise (which measurement systems and decoding algorithms should be used?). A project could be to develop new mental tasks that induce stronger/easier to decode signals, such as using broadband stimuli. Another project could be to develop new decoding methods better able to tease a weak signal from the background noise, such as adaptive-beam forming. Results for both would assessed by performing empirical studies with target users in one of the EEG/MEG/fMRI labs available in the institute.

Career prospects

Our Artificial Intelligence graduates have excellent job prospects and are often offered a job before they have actually graduated. Many of our graduates go on to do a PhD either at a major research institute or university with an AI department. Other graduates work for companies interested in cognitive design and research. Examples of companies looking for AI experts with this specialisation: Google, Facebook, IBM, Philips and the Brain Foundation. Some students have even gone on to start their own companies.

Job positions

Examples of jobs that a graduate of the specialisation in Computation in Neural and Artificial Systems could get:
- PhD researcher on bio-inspired computing
- PhD researcher on neural decoding
- PhD researcher on neural information processing
- Machine learning expert in a software company
- Company founder for brain-based computer games
- Hospital-based designer of assistive technology for patients
- Policy advisor on new developments in neurotechnology
- Software developer for analysis and online visual displays of brain activity

Internship

Half of your second year consists of an internship, giving you plenty of hands-on experience. We encourage students to do this internship abroad, although this is not mandatory. We do have connections with companies abroad, for example in China, Sweden and the United States.

See the website http://www.ru.nl/masters/ai/computation

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Learning how to build the intelligence used to power the future of the Web.
The Web has provided us with novel ways to maintain our social networks, rapidly search for information, and make purchases from the comfort of our own home. Most of us take these technologies for granted. However, for the Web to function as it does numerous problems had to be solved: which pages should surface given your search query? Which status updates will you enjoy most? Or, how do we make sure you find the products that you where looking for?
These questions are solved using a combination of machine learning, and an understanding of users. As our use of the Web steadily grows, new questions are continuously emerging. Smarter and faster solutions to empower an intelligent Web are needed. In the Master’s specialisation in Web and Language Interaction you’ll learn the building blocks you’ll need to answer resolve future problems that arise on the Web. In this you’ll learn to understand the psychological, technical and statistical aspect of data science and other Web issues.
The key course in this specialisation is the new AI at the Webscale course, in which AI techniques are studied in the context of streaming and massive data. This course is complemented by the App-Lab course, aimed at understanding how Apps are set-up, built and evaluated. Covering human cognition, a choice of courses in psycho-linguistics is offered in line with the broad expertise within the Donders Institute.

See the website http://www.ru.nl/masters/ai/web

Why study Web and Language Interaction at Radboud University?

- Our cognitive focus leads to a highly interdisciplinary AI programme where students gain skills and knowledge from a number of different areas such as mathematics, computer science, psychology and neuroscience combined with a core foundation of artificial intelligence.

- This specialisation offers plenty of room to create a programme that meets your own academic and professional interests.

- Exceptional students who choose this specialisation have the opportunity to study for a double degree in Artificial Intelligence together with the specialisation in Data Science. This will take three instead of two years.

- Together with the world-renowned Donders Institute, the Max Planck Institute and various other leading research centres in Nijmegen, we train our students to become excellent researchers in AI.

- To help you decide on a research topic there is a semi-annual Thesis Fair where academics and companies present possible project ideas. Often there are more project proposals than students to accept them, giving you ample choice. We are also open to any of you own ideas for research.

- Our AI students are a close-knit group; they have their own room in which they often get together to debate and develop their projects. Every student also receives personal guidance and supervision from a member of our expert staff.

Our approach to this field

Language Information and Communication Technology lies at the basis of innumerable innovations in our society and has provided remarkable new services (like social media) and new products (like smart phones and tablets). Traditionally, applications of Artificial Intelligence used to be limited to micro worlds and toy systems. The horizon has now been widely extended to distribute mass applications of AI techniques. These developments are supported by a general availability of computation power and connectivity in the form of the web, social media, big data, wireless, and mobile platforms with input and output in many modalities.

Human-human and human-computer communication can be found in natural language applications like in the speech driven free-text systems such as Watson, and Siri, in brand sentiment detection and epidemic monitoring from tweets. But communication is also crucial for web applications and Apps that personalise information and make it accessible with other means. Examples thereof are voter guides, recommendation systems, click stream analysis, crowd sourcing and demand aggregation, e-therapy, e-inclusion, avatars with speech synthesis and recognition, gesture and emotion. Technical issues are e.g. map/ reduce architecture for massive data processing and emerging technologies like the semantic web.

Career prospects

Our Artificial Intelligence graduates have excellent job prospects and are often offered a job before they have actually graduated. Many of our graduates go on to do a PhD either at a major research institute or university with an AI department. Other graduates work for companies interested in cognitive design and research. Examples of companies looking for AI experts with this specialisation: Booking.com, Webpower, Google, Facebook, Philips, Booking.com, Philips, Rabobank. Some students have even gone on to start their own companies.

Job positions

Examples of jobs that a graduate of the specialisation in Web and Language Interaction could get:
- PhD researcher, for example, on enhancing speech recognition using semantic knowledge or in user interaction design for patient doctor communication in a virtual hospital
- Data Scientist in a web start-up
- Developer for Computer Aided Language Learning
- EU R&D programme leader on machine translation of natural language
- Developer of intelligent software for music studios

Internship

Half of your second year consists of an internship, giving you plenty of hands-on experience. We encourage students to do this internship abroad, although this is not mandatory. We do have connections with companies abroad, for example in China, Finland and the United States.

See the website http://www.ru.nl/masters/ai/web

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Overview

Understanding naturally intelligent systems, building artificially intelligent systems, and improving the interactions between humans and artificial systems.

As humans, we may be intrigued by the complexity of any daily activity. How do we perceive, act, decide, and remember? On the one hand, if we understand how our own intelligence works, we can use this knowledge to make computers smarter. On the other hand, by making computers behave more like humans, we learn more about how our own cognition works.

The AI Master’s programme at Radboud University has a distinctly cognitive focus. This cognitive focus leads to a highly interdisciplinary programme where students gain skills and knowledge from a number of different areas such as mathematics, computer science, psychology and neuroscience combined with a core foundation of artificial intelligence.

See the website http://www.ru.nl/masters/ai

Scientific and practical applications

Slowly the human brain has been revealing its mystery to the scientific community. Now that we are actually able to model and stimulate aspects of cognition, AI researchers have gained a deeper understanding of cognition. At the world-renowned Donders Institute, the Max Planck Institute and various other leading research centres, we train our students to become excellent researchers in this area.

At Radboud University we also teach students how to develop practical applications that will become the next generation of products, apps, therapies and services. Our department has been awarded several prizes for its pioneering role in bringing innovations from science to society, e.g. in Assistive Technology for people with disabilities. You’ll be taught the skills needed to conduct and steer such innovation processes. Many Master’s research projects have both a scientific and a practical component.

Specialisations

Computational modelling is the central methodology taught and used in this programme. Depending on the area of study, the computational models can range from behavioural models of millions of individuals interacting on the web, to functional models of human or robot decision-making, to models of individual or networks of artificial neurons. At Radboud University we offer the following three specialisations (on campus simply known as Computation, Robot and Web):

- Computation in Neural and Artificial Systems
Learn how to create artificial information systems that mimic biological systems as well as how to use theoretical insights from AI to better understand cognitive processing in humans.

- Robot Cognition
Understand all aspects of Human-Robot interaction: the programming that coordinates a robot’s actions with human action as well the human appreciation and trust in the robot.

- Web and Language Interaction
Learn how to build the intelligence used to power the future of the Web.

Research project and Internship

To finalise your AI master's programme, you have the choice of either an Internship (18EC) and Research Project (30EC) or a single larger Extended Research Project (48EC). During the internship you have the chance to acquire additional AI relevant skills either at a research lab or at a company. During the Research Projects phase, you get to put what you have learned during your master's programme into practice. You can perform your research work in the AI department, at other research departments at the University (e.g. the Behaviour Science Institute or Donders Institute) or at an external company (such as Philips or TNO). You are also encouraged to go abroad for your internship and/or research project (previously students have gone to Stanford University in California and Aldebaran Robotics in Paris). To help you decide on a thesis topic, there is an annual Thesis Fair where academics and companies present possible project ideas.

Job opportunities

Our Artificial Intelligence graduates have excellent job prospects and are often offered a job before they have actually graduated. Many of our graduates go on to do a PhD either at a major research institute or a university with an AI department. Other graduates have started their own companies or work for companies interested in cognitive design and research.

Find out how to apply here http://www.ru.nl/masters/ai

Meet Radboud University

- Information for international students
Radboud University would like to meet you in your country (http://www.ru.nl/meetus) in order to give all the information you need and to answer any questions you might have about studying in the Netherlands. In the next few months, an advisor of Radboud University will be attending fairs in various countries, always accompanied by a current or former student.
Furthermore, we understand if you would like to see the Radboud Campus and the city of Nijmegen, which is why we organise an Master's Open Day for international students (http://www.ru.nl/openday) which will take place on 5 March 2016.

- Information for Dutch students
Radboud University offers students in the Netherlands plenty of opportunities to get more information on your programme of choice, or get answers to any questions you might have and more. Apart from a Master's Evening and a Master's Day, we also organise Orientation Days and a Master’s Afternoon for HBO students.

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Understanding all aspects of Human-Robot interaction: the programming that coordinates a robot’s actions with human action as well the human appreciation and trust in the robot.
At present, there are many sensors and actuators in every device – so they may become embedded in a physical reality. For robots that move around in a specific setting there is a pressing need for the development of proper methods of control and joint-action. The embedded, embodied nature of human cognition is an inspiration for this, and vice versa. Computational modelling of such tasks can give insight into the nature of human mental processing. In the Master’s specialisation in Robot Cognition you’ll learn all about the sensors, actuators and the computational modelling that connects them.
Making sense of sensor data – developing artificial perception – is no trivial task. The perception, recognition and even appreciation of sound stimuli for speech and music (i.e. auditory scene analysis) require modelling and representation at many levels and the same holds for visual object recognition and computer vision. In this area, vocal and facial expression recognition (recognition of emotion from voices and faces) is a rapidly growing application area. In the area of action and motor planning, sensorimotor integration and action, there are strong links with research at the world-renowned Donders Centre for Cognition.
At Radboud University we also look beyond the technical side of creating robots that can move, talk and interpret emotions as humans do. We believe that a robot needs to do more than simply function to its best ability. A robot that humans distrust will fail even if it is well programmed. Culture also plays a role in this; people in Japan are more open to the possibilities of robots than in, for example, the Netherlands. We will teach you how to evaluate humans’ attitudes towards a robot in order to use that information to create robots that will be accepted and trusted and therefore perform even better.

See the website http://www.ru.nl/masters/ai/robot

Why study Robot Cognition at Radboud University?

- We offer a great mix of technical and social aspects of robot cognition.

- This programme focuses on programming robot behaviours and evaluating them rather than building the robots themselves. We teach you to programme robots that will be used in close contact with human beings, for example in healthcare and education, rather than in industry.

- Our cognitive focus leads to a highly interdisciplinary AI programme where students gain skills and knowledge from a number of different areas such as mathematics, computer science, psychology and neuroscience combined with a core foundation of artificial intelligence.

- This specialisation offers plenty of room to create a programme that meets your own academic and professional interests.

- Together with the world-renowned Donders Institute, the Max Planck Institute and various other leading research centres in Nijmegen, we train our students to become excellent researchers in AI.

- To help you decide on a research topic there is a semi-annual Thesis Fair where academics and companies present possible project ideas. Often there are more project proposals than students to accept them, giving you ample choice. We are also open to any of you own ideas for research.

- Our AI students are a close-knit group; they have their own room in which they often get together to interact, debate and develop their ideas. Every student also receives personal guidance and supervision from a member of our expert staff.

Our research in this field

The programme is closely related to the research carried out in the internationally renowned Donders Institute for Brain, Cognition and Behaviour. This institute has several unique facilities for brain imaging using EEG, fMRI and MEG. You could also cooperate with the Behavioural Science Institute and work in its Virtual Reality Laboratory, which can be used to study social interaction between humans and avatars.

An example of a possible thesis subject:
- Engaging human-robot interactions in healthcare for children and/or the elderly
Social robots are often deployed with 'special' user groups such as children and elderly people. Developing and evaluating robot behaviours for these user groups is a challenge as a proper understanding of their cognitive and social abilities is needed. Depending on the task, children for example need to be engaged and encouraged in a different way than adults do. What are effective robot behaviours and strategies to engage children and/or elderly people? How can these robot behaviours be evaluated in a proper way?

Career prospects

Our Artificial Intelligence graduates have excellent job prospects and are often offered a job before they have actually graduated. Many of our graduates go on to do a PhD either at a major research institute or university with an AI department. Other graduates work for companies interested in cognitive design and research. Examples of companies looking for AI experts with this specialisation: Philips, Siemens, Honda, Mercedes, Google. Some students have even gone on to start their own companies.

Job positions

Examples of jobs that a graduate of the specialisation in Robot Cognition could get:
- PhD Researcher on Cognitive-Affective Modelling for Social Robots
- PhD Researcher on Automatic analysis of human group behaviour in the presence of robots
- PhD Researcher on Automatic analysis of affective quality of conversations in human-robot interaction
- Advisor and innovation manager in the healthcare industry
- Social robotics and affective computing for robots expressing emotions
- Developer of control algorithms for using optic flow in drones
- Advisor for start-up company on developing new uses for tactile displays
- Team member in design of emotion recognition and training for autistic children

Internship

Half of your second year consists of an internship, giving you plenty of hands-on experience. We encourage students to do this internship abroad, although this is not mandatory. We do have connections with companies abroad, for example in China, Finland and the United States.

See the website http://www.ru.nl/masters/ai/robot

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Artificial Intelligence is a well-established, exciting branch of computer science concerned with methods to make computers, or machines in general, intelligent - so that they are able to learn from experience, to derive implicit knowledge from the one given explicitly, to understand natural languages such as English, Arabic, or Urdu, to determine the content of images, to work collaboratively together, etc. The techniques used in AI are as diverse as the problems tackled: they range from classical logic to statistical approaches to simulate brains.

This pathway reflects the diversity of AI in that it freely combines a number of themes related to AI techniques, namely Making Sense of Complex Data, Learning from Data, Reasoning and Optimisation, and Advanced Web Technologies.

Course description

Artificial Intelligence is a well-established, exciting branch of computer science concerned with methods to make computers, or machines in general, intelligent - so that they are able to learn from experience, to derive implicit knowledge from the one given explicitly, to understand natural languages such as English, Arabic, or Urdu, to determine the content of images, to work collaboratively together, etc. The techniques used in AI are as diverse as the problems tackled: they range from classical logic to statistical approaches to simulate brains.

This pathway reflects the diversity of AI in that it freely combines a number of themes related to AI techniques, namely Making Sense of Complex Data, Learning from Data, Reasoning and Optimisation, and Advanced Web Technologies.

Teaching and learning

Computational thinking is becoming increasingly pervasive and is informing our understanding of phenomena across a range of areas; from engineering and physical sciences, to business and society. This is reflected in the way the Manchester course is taught, with students able to choose from an extremely broad range of units that not only cover core computer science topics, but that draw on our interdisciplinary research strengths in areas such as Medical and Health Sciences, Life Sciences and Humanities.

Coursework and assessment

Lectures and seminars are supported by practical exercises that impart skills as well as knowledge. These skills are augmented through an MSc project that enables students to put into practice the techniques they have been taught throughout the course.

Facilities

-Newly refurbished computing labs furnished with modern desktop computers
-Access to world leading academic staff
-Collaborative working labs complete with specialist computing and audio visual equipment to support group working
-Over 300 Computers in the School dedicated exclusively for the use of our student
-An Advanced Interfaces Laboratory to explore real time collaborative working
-A Nanotechnology Centre for the fabrication of new generation electronic devices
-An e-Science Centre and Access Grid facility for world wide collaboration over the internet
-Access to a range of Integrated Development Environments (IDEs)
-Specialist electronic system design and computer engineering tools

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Your programme of study

If you want to get involved in our next industry revolution - Industry 4.0 this degree will go a long way to providing you with many skills needed in this high growth industry area which has continued from where the mass communications revolution. You must have covered either computer science or electrical and electronic engineering as your first degree or a suitable combination to study this Master's degree. The digital age is changing the way we live, communicate, interact and our quality of life rapidly. Cloud based networks are now normal, autonomous vehicles are being explored, visual recognition, GIS aligning to our search interests, data mining to inform us automatically at any point in time what is happening around us and new methods to inform us of danger, awareness, alerts and so on.

Artificial Intelligence provides in depth knowledge of data mining, natural language, information visualisation and communication used in Industry 4.0 innovation industries such as autonomous vehicles, sensor data collection and computation, visual computer recognition software and machine to machine technologies.

Courses listed for the programme

SEMESTER 1
Compulsory Courses
Foundations in AI
Machine Learning
Evaluation Systems of AI Systems
Engineering of AI Systems

SEMESTER 2
Compulsory Courses
Data Mining and Visualisation
Natural Language Generation
Software Agents and Multi-Agent Systems
Knowledge Representation and Reasoning

SEMESTER 3
You can broaden and deepen your skills with industry client opportunities where possible

Find out more detail by visiting the programme web page
https://www.abdn.ac.uk/study/postgraduate-taught/degree-programmes/1034/artificial-intelligence/

Why study at Aberdeen?

• AI or Artificial Intelligence is part of a major industrial revolution globally, linking to the Internet of Things
• Aberdeen gives you a strong worldwide reputation for teaching in computing science, data science and natural language
generation
• You can be involved in cutting edge innovations which will shape our world in the future

Where you study

• University of Aberdeen

International Student Fees 2017/2018

Find out about fees:
https://www.abdn.ac.uk/study/international/tuition-fees-and-living-costs-287.php

*Please be advised that some programmes have different tuition fees from those listed above and that some programmes also have additional costs.

Scholarships

View all funding options on our funding database via the programme page
https://www.abdn.ac.uk/study/postgraduate-taught/finance-funding-1599.php
https://www.abdn.ac.uk/funding/

Living in Aberdeen

Find out more about:
• Your Accommodation
• Campus Facilities
• Aberdeen City
• Student Support
• Clubs and Societies

Find out more about living in Aberdeen:
https://abdn.ac.uk/study/student-life

Living costs
https://www.abdn.ac.uk/study/international/finance.php

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What is intelligent behaviour? How can robots communicate with each other? In this programme you will learn how to design and implement intelligent systems.

The core topics in The Master's programme Artificial Intelligence are: autonomous perceptive systems, cognitive robotics and multi-agent systems.

- Autonomous Systems
A robot taking samples and collecting information on the moon is an example of an autonomous system. It operates and carries out missions independently. Regardless of their surroundings, it responds with a certain intelligence. While traditional AI focuses on cognition and reasoning as isolated abilities, we strongly believe in perception as an active behavior, which is integrated into general cognition.

- Cognitive Robotics
The courses taught in the area of cognitive robotics are related to research in social robotics, to the origin of robotic communication and to the way in which robots recognize movement. Research is conducted at the Artificial Intelligence and Cognitive Engineeringinstitute.

- Multi-agent Systems
When a team of robots play footbal they have to communicate and cooperate with each other. This is an example of a multi-agent system. When designing these systems, techniques from computing science and logic are combined with knowledge about the interaction amongst humans and animals.

Why in Groningen?

- Be part of a Programme with excellent reviews
- Challenging graduation projects

Job perspectives

Once you have obtained your Master's degree in Artificial Intelligence, you can apply your skills in research & development, for instance air traffic and space labs, where you make sure that intelligent and innovative technologies are used during the design process. You could also choose to get a job at a research institute where you work as a researcher. This can be done at a university (PhD) or at a research institute like TNO. About 50% of our students chooses a career as a scientist.

Where do graduated master AI students work at the moment? Maarten van Grachten and Mathijs Homminga did the AI master in the old doctoral program and they specialized in very different directions. Mathijs works as a software engineer at the IT-company Evermind. He programs and implements innovative IT-projects for shops. Maarten is doing a PhD in Barcelona where he investigates how a computer can compose jazz music.

Job examples

- Industrial Research & Development
- PhD research position
- Software engineer

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Our groundbreaking MSc has been developed in response to a pressing need to offer a high quality postgraduate programme serving the industries of computer games and entertainment, with an emphasis on programming, maths and graphics, business, IP, entrepreneurship, team management, 3D animation, AI and physics in games- http://www.gold.ac.uk/pg/msc-computer-games-entertainment/

The computer games and entertainment business is a fast growing multi-billion dollar worldwide business, with games platforms ranging from Playstation 4, Xbox One, Nintendo Wii U, mobile and handhelds including iPhone, iPad and Android phones, PC-based, and massively multiplayer online games (MMOG) involving tens of thousands of people.

With ongoing strong demand for graduate computer games programmers from the UK and abroad, this MSc will produce graduates who are well positioned to get a job in this exciting worldwide industry. Potential employers include EA, Ubisoft, Sony, Activision, Microsoft, Cinesite, Framestore, and many more.

The programme is delivered by a mix of professionals from the industry and from the research world. We work closely with industry leaders to offer internships at studios including Sega and Sony.

In a wider sense, the influence of computer games programming is spreading to other digital media industries outside games, including gamification and the medical sector, games based learning, new forms of social networking and the interactive visualisation of scientific and live financial business data. Computer games are starting to fundamentally change the way people interact with computerised systems.

Partnership: Sony‌‌

‌Our MSc in Computer Games & Entertainment is part of the PlayStation®First Academic Partnership Programme offered by Sony Computer Entertainment Europe (SCEE) uk.playstation.com. Our course provides students with unique access to PlayStation® professional development hardware (dev kits) and software (SDK) to equip students with industry relevant game development skills across PlayStation®3 and PlayStation® Vita. http://www.worldwidestudios.net/london

Placement: Supermassive Games

"Following two years of successful placements at Supermassive Games, which resulted in full time jobs, we are looking forward to inviting Goldsmiths students to take part in our internship assessment day again this year."
Jonathan Amor, Director of Technology, Supermassive Games
‌

Placement: Reflections - a Ubisoft studio

"We are delighted to announce that Reflections, a Ubisoft studio, will be taking on two Goldsmiths MSc Computer Games and Entertainment Programming students for Internship."
Dr Chris Jenner, Expert Programmer

Placement: Rebellion

"Having now placed four interns from Goldsmiths here at Rebellion, two of which have gone on to become permanent members of staff, we are very much looking forward to future applications from talented and creative Goldsmiths MSc Computer Games students”
Jason Kingsley OBE, CEO and Creative Director of Rebellion

Rebellion is one of Europe’s largest independent game developer-publishers, with their own state of the art cross-platform games engine and toolset. Rebellion’s latest number one hit was Sniper Elite 3, and they also publish the legendary 2000AD comic featuring Judge Dredd.

Placement: The Creative Assembly (SEGA)

Following two continuous years of The Creative Assembly (SEGA) successfully taking Goldsmiths MSc Games Programming Students on placements we are pleased to announce that we have reserved a minimum of three placements for Goldsmiths MSc students starting the course in September 2013, on site during the period May to September 2014. Subject to interview/ portfolio process”. Martin Servantes Director of Operations & Finance

Leading UK Developer Creative Assembly is the developer of the hit game series Total War. They are currently working on a new cross-platform title based on the Alien IP. Based in Horsham.

Placement: Jagex Games Studio

"Jagex Games Studio in Cambridge is looking forward to receiving applications from Goldsmiths’ talented MSc Games and Entertainment students for their summer internships in 2014”.
Sue Stather, Graduate Recruitment Specialist, Jagex Games Studio (RuneScape and Transformers Universe MMO Development Studio)

Placement: Roll 7

Roll7 is a New Cross-based indie video games developer and has been offering placements to Goldsmiths MSc Games students for three years. Roll7 is just about to release its first console title OlliOll, exclusively for PSVita, and we are looking for another 1 or 2 Goldsmiths programming interns for 2014 to work on a Sony backed PS4/Vita cross-play title.

Contact the department

If you have specific questions about the degree, contact the Department of Computing.

Structure

Final Project & Dissertation
During this final project, you will undertake a project towards your dissertation, typically over the Spring-Summer period (May to September). We offer three options to our students:

Individual research project:

This is based on a research theme selected by you and agreed upon by the lecturing team. Recent examples include:
Building a cheap kinect-like gesture tracking system
AI (rule-based) platform for game level design
Software development for our mobile technology projects (iPhone based)
Assessment
Mainly based on coursework (involving programming), essays, final project and dissertation; some lecturers may also conduct exams/quizzes.

Attendance

The taught programme is organised into three terms (full-time). The Autumn term runs from early October to mid-December, the Winter/Spring term from mid-January to the end of March, and the Summer term runs, typically, from late April to mid-September. Taught modules are given during the Autumn and Winter/Spring terms, while the Final Project takes place during a Summer term (in the second year for part-time students).

This programme is focused on providing you with the skills and experience needed to secure a job in the computer games industry.

Skills

You'll develop excellent games programming skills. These skills are highly transferrable, as games programming is viewed by other industries as being very demanding and requiring a high level of technical ability.

Careers

The global computer games industry is valued at 60 billion USD and is predicted to continuously grow in years to come. It's a mature industry with companies such as EA, Ubisoft, and Blizzard Activision giving long-term career prospects, shares, and benefits. There is a big skills shortage in this growing sector.

Placements provided by our industry partners

Asylum Entertainment
Climax Studios
The Creative Assembly
Geomerics
IdeaWorks Game Studio (Now Marmalade Game Studio)
Playmob
Rebellion
Reflections - a Ubisoft studio
Roll7
SEGA Sports Interactive
Sony Computer Entertainment Europe

Alumni

See what some of our graduates have gone on to do on our alumni news page.

100% employment

All of the graduates from the 2012/13 MSc in Computer Games & Entertainment course have secured placements at UK computer games companies.

Funding

Please visit http://www.gold.ac.uk/pg/fees-funding/ for details.

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On City's MSc in Computer Games Technology you can develop specialist technical skills for a career in the Computer Games Industry.

Who is it for?

This course is aimed at students with a passion for computer games and a strong interest in programming. It is designed for students with an undergraduate degree in a numerate subject with substantial computing content, or those who wish to update their skills after a time in industry as a computing professional.

Objectives

The course is designed for you to develop:
-Strong technical skills suitable for professional programming roles in the game industry.
-Specialist knowledge in computer graphics, AI, physics and audio.
-The ability to design and build game engines from scratch in industry standard languages, including C++.
-Knowledge of the games development process, including the pitch, design, and use of a game engine to build a demo.
-Experience of the planning, management and execution of a major games technology project.

Academic facilities

With over 1,300 workstations, the on-campus computer rooms provide a valuable learning resource and give an opportunity for individuals to do coursework and projects. Computers have games development software including:
-Unity3D
-Unreal
-Microsoft Visual Studio
-Microsoft XNA Game Studio
-MonoDevelop
-MonoGame
-NShader
-FMOD Studio
-FMOD Studio API
-OGRE SDK
-WildMagic Geometric Tools
-Blender
-Adobe Photoshop.

City has recently invested in a new computer lab equipped with high specification NVidia GPUs.

Through City's Interaction Lab and the Department of Computing, there is hardware that can be used for student projects, including:
-Oculus Rift VR Headset
-Emotiv Epoc EEG Headset
-Neurosky Mindwave EEG Headset
-X-Box One Kinect Sensor
-X-Box 360 Kinect Sensor
-Leap Motion (Gestural input device)
-Affectiva Q Band Galvanic Skin Response sensor
-Tobii X-60 Eye Tracker

Placements

As a postgraduate student on a Computing and Information Systems course, you will have the opportunity to complete up to six months of professional experience as part of your degree.

Our longstanding internship scheme gives you the chance to apply the knowledge and skills gained from your taught modules within a real business environment. An internship also provides you with professional development opportunities that enhance your technical skills and business knowledge.

Internships delivered by City, University of London offer an exceptional opportunity to help you stand out in the competitive IT industry job market. The structure of the course extends the period for dissertation submission to January, allowing you to work full-time for up to six months. You will be supported by our outstanding Professional Liaison Unit (PLU) should you wish to consider undertaking this route.

Teaching and learning

The teaching and learning methods we use mean that your specialist knowledge and autonomy increase as you progress through each module. Active researchers guide your progress in the areas of Games Development, Computer Graphics, Artificial Intelligence and Audio, which culminates with an individual project. This is an original piece of research conducted with academic supervision, but largely independently and, where appropriate, in collaboration with industrial partners.

Taught modules are delivered through a series of 20 hours of lectures and 10 hours of tutorials/laboratory sessions. Lectures are normally used to:

present and exemplify the concepts underpinning a particular subject;
highlight the most significant aspects of the syllabus;
indicate additional topics and resources for private study.
Tutorials help you develop the skills to apply the concepts we have covered in the lectures. We normally achieve this through practical problem solving contexts.

Laboratory sessions give you the opportunity to apply concepts and techniques using state-of-the-art software, environments and development tools. In addition, City’s online learning environment Moodle contains resources for each of the modules from lecture notes and lab materials, to coursework feedback, model answers, and an interactive discussion forum.

We expect you to study independently and complete coursework for each module. This should amount to approximately 120 hours per module if you are studying full time. Modules are assessed through written examination and coursework, where you will need to answer theoretical and practical questions to demonstrate that you can analyse and apply computer games technology methods.

The individual project is a substantial task. It is your opportunity to develop an autonomous research-related topic under the supervision of an academic member of staff. This is the moment when you can apply your learning to solve a real-world problem, designing and implementing a solution and evaluating the result. At the end of the project you submit a substantial MSc project report, which becomes the mode of assessment for this part of the programme.

Modules

The programme is composed of eight taught modules and a final project.

The eight modules provide you with a firm grounding in computer games technology, including mathematics, programming, and game engines and architecture along with specialist topics in computer graphics, physics, AI, and audio.

The project component gives you an opportunity to carry out an extended piece of work under the supervision of one of our specialist academic and research staff, at the cutting edge of games technology, in an industrial or academic context.

Core Modules - there are eight Core Modules.
-Games development process
-Computer game architectures
-Computer graphics
-Game Physics and Artificial Intelligence
-Digital Signal Processing and Audio Programming
-Programming in C++
-Systems Specification
-Research, Methods and Professional Issues

Career prospects

Graduates are equipped with advanced knowledge and skills in a range of topics in games technology in preparation for a career in computer games development.

Alumni of the course are working in companies including Rockstar, Sony Computer Entertainment, Electronic Arts, and Codemasters, as well as start-ups and independent studios.

City has a dedicated incubation space, called the Hangout, located in the heart of Tech City that is specially designed for student entrepreneurs from City, University of London who want to get their idea off the ground.

Professional roles include:
-3D Graphics Programmer
-Audio Programmer
-Physics Programmer
-Artificial Intelligence Programmer
-Simulation and Game Engine Programmer
-User Interface Programmer
-Tools and Utility Programmer
-Scripting Languages Programmer
-Networking Specialist
-Porting Programmer

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Through a mix of lectures, laboratories, clinical demonstrations and hospital visits, our MSc in Medical Imaging will develop you as a professional, enhancing your ability to take on new challenges with confidence. This programme is run together with the Department of Physics.

PROGRAMME OVERVIEW

Medical imaging is a rapidly-growing discipline within the healthcare sector, involving clinicians, physicists, computer scientists and those in IT industries.

This programme delivers the expertise you'll need to forge a career in medical imaging, including radiation physics, image processing, biology, computer vision, pattern recognition, artificial intelligence and machine learning.

PROGRAMME STRUCTURE

This programme is studied full-time over 12 months and part-time over 48 months. It consists of eight taught modules and an extended project. The following modules are indicative, reflecting the information available at the time of publication. Please note that not all modules described are compulsory and may be subject to teaching availability and/or student demand.
-Image Processing and Vision
-Professional Skills for Clinical Science and Engineering
-Radiation Biology
-Radiation Physics
-AI and AI Programming
-Computer Vision and Pattern Recognition
-Diagnostic Apps of Ionising Radiation
-Non-Ionising Radiation Imaging
-Engineering Professional Studies 1
-Engineering Professional Studies 2
-Extended Project

FACILITIES, EQUIPMENT AND SUPPORT

To support your learning, we hold regular MSc group meetings where any aspect of the programme, technical or non-technical, can be discussed in an informal atmosphere. This allows you to raise any problems that you would like to have addressed and encourages peer-based learning and general group discussion.

We provide computing support with any specialised software required during the programme, for example, Matlab.

The Department’s student common room is also covered by the university’s open-access wireless network, which makes it a very popular location for individual and group work using laptops and mobile devices. There is also a Faculty quiet room for individual study.

We pride ourselves on the many opportunities that we provide to visit collaborating hospitals. These enable you to see first-hand demonstrations of medical imaging facilities and to benefit from lectures by professional practitioners.

To support material presented during the programme, you will also undertake a selection of ultrasound and radiation detection experiments, hosted by our sister MSc programme in Medical Physics.

EDUCATIONAL AIMS OF THE PROGRAMME

The taught postgraduate Degree Programmes of the Department are intended both to assist with professional career development within the relevant industry and, for a small number of students, to serve as a precursor to academic research.

Our philosophy is to integrate the acquisition of core engineering and scientific knowledge with the development of key practical skills (where relevant).

To fulfil these objectives, the programme aims to:
-Attract well-qualified entrants, with a background in Electronic Engineering, Physical Sciences, Mathematics, Computing & Communications, from the UK, Europe and overseas
-Provide participants with advanced knowledge, practical skills and understanding applicable to the MSc degree
-Develop participants' understanding of the underlying science, engineering, and technology, and enhance their ability to relate this to industrial practice
-Develop participants' critical and analytical powers so that they can effectively plan and execute individual research/design/development projects
-Provide a high level of flexibility in programme pattern and exit point
-Provide students with an extensive choice of taught modules, in subjects for which the Department has an international and UK research reputation

PROGRAMME LEARNING OUTCOMES

The programme provides opportunities for students to develop and demonstrate knowledge and understanding, skills, qualities and other attributes in the following areas:

General transferable skills
-Be able to use computers and basic IT tools effectively
-Information retrieval. Be able to retrieve information from written and electronic sources
-Be able to apply critical but constructive thinking to received information
-Be able to study and learn effectively
-Be able to communicate effectively in writing and by oral presentations
-Be able to present quantitative data effectively, using appropriate methods
-Be able to manage own time and resources
-Be able to develop, monitor and update a plan, in the light of changing circumstances
-Be able to reflect on own learning and performance, and plan its development/improvement, as a foundation for life-long learning

Underpinning learning
-Know and understand scientific principles necessary to underpin their education in electronic and electrical engineering, to enable appreciation of its scientific and engineering content, and to support their understanding of historical, current and future developments
-Know and understand the mathematical principles necessary to underpin their education in electronic and electrical engineering and to enable them to apply mathematical methods, tools and notations proficiently in the analysis and solution of engineering problems
-Be able to apply and integrate knowledge and understanding of other engineering disciplines to support study of electronic and electrical engineering

Engineering problem-solving
-Understand electronic and electrical engineering principles and be able to apply them to analyse key engineering processes
-Be able to identify, classify and describe the performance of systems and components through the use of analytical methods and modelling techniques
-Be able to apply mathematical and computer-based models to solve problems in electronic and electrical engineering, and be able to assess the limitations of particular cases
-Be able to apply quantitative methods relevant to electronic and electrical engineering, in order to solve engineering problems
-Understand and be able to apply a systems approach to electronic and electrical engineering problems

Engineering tools
-Have relevant workshop and laboratory skills
-Be able to write simple computer programs, be aware of the nature of microprocessor programming, and be aware of the nature of software design
-Be able to apply computer software packages relevant to electronic and electrical engineering, in order to solve engineering problems

Technical expertise
-Know and understand the facts, concepts, conventions, principles, mathematics and applications of the range of electronic and electrical engineering topics he/she has chosen to study
-Know the characteristics of particular materials, equipment, processes or products
-Have thorough understanding of current practice and limitations, and some appreciation of likely future developments
-Be aware of developing technologies related to electronic and electrical engineering
-Have comprehensive understanding of the scientific principles of electronic engineering and related disciplines
-Have comprehensive knowledge and understanding of mathematical and computer models relevant to electronic and electrical engineering, and an appreciation of their limitations
-Know and understand, at Master's level, the facts, concepts, conventions, principles, mathematics and applications of a range of engineering topics that he/she has chosen to study
-Have extensive knowledge of a wide range of engineering materials and components
-Understand concepts from a range of areas including some from outside engineering, and be able to apply them effectively in engineering projects

Societal and environmental content
-Understand the requirement for engineering activities to promote sustainable development
-Be aware of the framework of relevant legal requirements governing engineering activities, including personnel, health, safety and risk (including environmental risk issues
-Understand the need for a high level of professional and ethical conduct in engineering

Employment context
-Know and understand the commercial and economic context of electronic and electrical engineering processes
-Understand the contexts in which engineering knowledge can be applied (e.g. operations and management, technology development, etc.)
-Understand appropriate codes of practice and industry standards
-Be aware of quality issues
-Be able to apply engineering techniques taking account of a range of commercial and industrial constraints
-Understand the basics of financial accounting procedures relevant to engineering project work
-Be able to make general evaluations of commercial risks through some understanding of the basis of such risks
-Be aware of the framework of relevant legal requirements governing engineering activities, including personnel, health, safety and risk (including environmental risk) issues

Research and development
-Understand the use of technical literature and other information sources
-Be aware of the need, in appropriate cases, for experimentation during scientific investigations and during engineering development
-Be able to use fundamental knowledge to investigate new and emerging technologies
-Be able to extract data pertinent to an unfamiliar problem, and employ this data in solving the problem, using computer-based engineering tools when appropriate
-Be able to work with technical uncertainty

Design
-Understand the nature of the engineering design process
-Investigate and define a problem and identify constraints, including environmental and sustainability limitations, and health and safety and risk assessment issues
-Understand customer and user needs and the importance of considerations such as aesthetics
-Identify and manage cost drivers
-Use creativity to establish innovative solutions
-Ensure fitness for purpose and all aspects of the problem including production, operation, maintenance and disposal
-Manage the design process and evaluate outcomes
-Have wide knowledge and comprehensive understanding of design processes and methodologies and be able to apply and adapt them in unfamiliar situations
-Be able to generate an innovative design for products, systems, components or processes, to fulfil new needs

Project management
-Be able to work as a member of a team
-Be able to exercise leadership in a team
-Be able to work in a multidisciplinary environment
-Know about management techniques that may be used to achieve engineering objectives within the commercial and economic context of engineering processes
-Have extensive knowledge and understanding of management and business practices, and their limitations, and how these may be applied appropriately

GLOBAL OPPORTUNITIES

We often give our students the opportunity to acquire international experience during their degrees by taking advantage of our exchange agreements with overseas universities.

In addition to the hugely enjoyable and satisfying experience, time spent abroad adds a distinctive element to your CV.

Read less

If you are intrigued by the acquisition, processing, analysis and understanding of computer vision, this Masters is for you.

The programme is offered by Surrey's Department of Electrical and Electronic Engineering, recognised for world-leading research in multimedia signal processing and machine learning.

PROGRAMME OVERVIEW

This degree provides in-depth training for students interested in a career in industry or in research-oriented institutions focused on image and video analysis, and deep learning.

State-of-the-art computer-vision and machine-learning approaches for image and video analysis are covered in the course, as well as low-level image processing methods.

Students also have the chance to substantially expand their programming skills through projects they undertake.

PROGRAMME STRUCTURE

This programme is studied full-time over 12 months and part-time over 48 months. It consists of eight taught modules and a standard project.

The following modules are indicative, reflecting the information available at the time of publication. Please note that not all modules described are compulsory and may be subject to teaching availability and/or student demand.
-Digital Signal Processing A
-Object Oriented Design and C++
-Image Processing and Vision
-Space Robotics and Autonomy
-Satellite Remote Sensing
-Computer Vision and Pattern Recognition
-AI and AI Programming
-Advanced Signal Processing
-Image and Video Compression
-Standard Project

EDUCATIONAL AIMS OF THE PROGRAMME

The taught postgraduate degree programmes of the Department of Electronic Engineering are intended both to assist with professional career development within the relevant industry and, for a small number of students, to serve as a precursor to academic research.

Our philosophy is to integrate the acquisition of core engineering and scientific knowledge with the development of key practical skills (where relevant). To fulfil these objectives, the programme aims to:
-Attract well-qualified entrants, with a background in Electronic Engineering, Physical Sciences, Mathematics, Computing and Communications, from the UK, Europe and overseas.
-Provide participants with advanced knowledge, practical skills and understanding applicable to the MSc degree
-Develop participants' understanding of the underlying science, engineering, and technology, and enhance their ability to relate this to industrial practice
-Develop participants' critical and analytical powers so that they can effectively plan and execute individual research/design/development projects
-Provide a high level of flexibility in programme pattern and exit point
-Provide students with an extensive choice of taught modules, in subjects for which the Department has an international and UK research reputation

Intended capabilities for MSc graduates
-Know, understand and be able to apply the fundamental mathematical, scientific and engineering facts and principles that underpin computer vision, machine learning as well as how they can be related to robotics
-Be able to analyse problems within the field computer vision and more broadly in electronic engineering and find solutions
-Be able to use relevant workshop and laboratory tools and equipment, and have experience of using relevant task-specific software packages to perform engineering tasks
-Know, understand and be able to use the basic mathematical, scientific and engineering facts and principles associated with the topics within computer vision, machine learning
-Be aware of the societal and environmental context of his/her engineering activities
-Be aware of commercial, industrial and employment-related practices and issues likely to affect his/her engineering activities
-Be able to carry out research-and-development investigations
-Be able to design electronic circuits and electronic/software products and systems

Technical characteristics of the pathway
This programme in Computer Vision, Robotics and Machine Learning aims to provide a high-quality advanced training in aspects of computer vision for extracting information from image and video content or enhancing its visual quality using machine learning codes.

Computer vision technology uses sophisticated signal processing and data analysis methods to support access to visual information, whether it is for business, security, personal use or entertainment. The core modules cover the fundamentals of how to represent image and video information digitally, including processing, filtering and feature extraction techniques.

An important aspect of the programme is the software implementation of such processes. Students will be able to tailor their learning experience through selection of elective modules to suit their career aspirations.

Key to the programme is cross-linking between core methods and systems for image and video analysis applications. The programme has strong links to current research in the Department of Electronic Engineering’s Centre for Vision, Speech and Signal Processing.

PROGRAMME LEARNING OUTCOMES

The Department's taught postgraduate programmes are designed to enhance the student's technical knowledge in the topics within the field that he/she has chosen to study, and to contribute to the Specific Learning Outcomes set down by the Institution of Engineering and Technology (IET) (which is the Professional Engineering body for electronic and electrical engineering) and to the General Learning Outcomes applicable to all university graduates.

General transferable skills
-Be able to use computers and basic IT tools effectively
-Be able to retrieve information from written and electronic sources
-Be able to apply critical but constructive thinking to received information
-Be able to study and learn effectively
-Be able to communicate effectively in writing and by oral presentations
-Be able to present quantitative data effectively, using appropriate methods

Time and resource management
-Be able to manage own time and resources
-Be able to develop, monitor and update a plan, in the light of changing circumstances
-Be able to reflect on own learning and performance, and plan its development/improvement, as a foundation for life-long learning

Underpinning learning
-Know and understand scientific principles necessary to underpin their education in electronic and electrical engineering, to enable appreciation of its scientific and engineering content, and to support their understanding of historical, current and future developments
-Know and understand the mathematical principles necessary to underpin their education in electronic and electrical engineering and to enable them to apply mathematical methods, tools and notations proficiently in the analysis and solution of engineering problems
-Be able to apply and integrate knowledge and understanding of other engineering disciplines to support study of electronic and electrical engineering

Engineering problem-solving
-Understand electronic and electrical engineering principles and be able to apply them to analyse key engineering processes
-Be able to identify, classify and describe the performance of systems and components through the use of analytical methods and modelling techniques
-Be able to apply mathematical and computer-based models to solve problems in electronic and electrical engineering, and be able to assess the limitations of particular cases
-Be able to apply quantitative methods relevant to electronic and electrical engineering, in order to solve engineering problems
-Understand and be able to apply a systems approach to electronic and electrical engineering problems

Engineering tools
-Have relevant workshop and laboratory skills
-Be able to write simple computer programs, be aware of the nature of microprocessor programming, and be aware of the nature of software design
-Be able to apply computer software packages relevant to electronic and electrical engineering, in order to solve engineering problems

Technical expertise
-Know and understand the facts, concepts, conventions, principles, mathematics and applications of the range of electronic and electrical engineering topics he/she has chosen to study
-Know the characteristics of particular materials, equipment, processes or products
-Have thorough understanding of current practice and limitations, and some appreciation of likely future developments
-Be aware of developing technologies related to electronic and electrical engineering
-Have comprehensive understanding of the scientific principles of electronic engineering and related disciplines
-Have comprehensive knowledge and understanding of mathematical and computer models relevant to electronic and electrical engineering, and an appreciation of their limitations
-Know and understand, at Master's level, the facts, concepts, conventions, principles, mathematics and applications of a range of engineering topics that he/she has chosen to study
-Have extensive knowledge of a wide range of engineering materials and components
-Understand concepts from a range of areas including some from outside engineering, and be able to apply them effectively in engineering projects

Societal and environmental context
-Understand the requirement for engineering activities to promote sustainable development
-Relevant part of: Be aware of the framework of relevant legal requirements governing engineering activities, including personnel, health, safety and risk (including environmental risk issues
-Understand the need for a high level of professional and ethical conduct in engineering

Employment context
-Know and understand the commercial and economic context of electronic and electrical engineering processes
-Understand the contexts in which engineering knowledge can be applied (e.g. operations and management, technology development, etc.)
-Be aware of the nature of intellectual property
-Understand appropriate codes of practice and industry standards
-Be aware of quality issues
-Be able to apply engineering techniques taking account of a range of commercial and industrial constraints
-Understand the basics of financial accounting procedures relevant to engineering project work
-Be able to make general evaluations of commercial risks through some understanding of the basis of such risks
-Be aware of the framework of relevant legal requirements governing engineering activities, including personnel, health, safety and risk (including environmental risk) issues

Research and development
-Understand the use of technical literature and other information sources
-Be aware of the need, in appropriate cases, for experimentation during scientific investigations and during engineering development
-Be able to use fundamental knowledge to investigate new and emerging technologies
-Be able to extract data pertinent to an unfamiliar problem, and employ this data in solving the problem, using computer-based engineering tools when appropriate
-Be able to work with technical uncertainty

Design
-Understand the nature of the engineering design process
-Investigate and define a problem and identify constraints, including environmental and sustainability limitations, and health and safety and risk assessment issues
-Understand customer and user needs and the importance of considerations such as aesthetics
-Identify and manage cost drivers
-Use creativity to establish innovative solutions
-Ensure fitness for purpose and all aspects of the problem including production, operation, maintenance and disposal
-Manage the design process and evaluate outcomes
-Have wide knowledge and comprehensive understanding of design processes and methodologies and be able to apply and adapt them in unfamiliar situations
-Be able to generate an innovative design for products, systems, components or processes, to fulfil new needs

Project management
-Be able to work as a member of a team
-Be able to exercise leadership in a team
-Be able to work in a multidisciplinary environment
-Know about management techniques that may be used to achieve engineering objectives within the commercial and economic context of engineering processes
-Have extensive knowledge and understanding of management and business practices, and their limitations, and how these may be applied appropriately

FACILITIES, EQUIPMENT AND SUPPORT

To support your learning, we hold regular MSc group meetings where any aspect of the programme, technical or non-technical, can be discussed in an informal atmosphere. This allows you to raise any problems that you would like to have addressed and encourages peer-based learning and general group discussion.

We provide computing support with any specialised software required during the programme, for example, Matlab. The Faculty’s student common room is also covered by the University’s open-access wireless network, which makes it a very popular location for individual and group work using laptops and mobile devices.

Specialist experimental and research facilities, for computationally demanding projects or those requiring specialist equipment, are provided by the Centre for Vision, Speech and Signal Processing (CVSSP).

CAREER PROSPECTS

Computer vision specialists are be valuable in all industries that require intelligent processing and interpretation of image and video. This includes industries in directly related fields such as:
-Multimedia indexing and retrieval (Google, Microsoft, Apple)
-Motion capture (Foundry)
-Media production (BBC, Foundry)
-Medical Imaging (Siemens)
-Security and Defence (BAE, EADS, Qinetiq)
-Robotics (SSTL)

Studying for Msc degree in Computer Vision offers variety, challenge and stimulation. It is not just the introduction to a rewarding career, but also offers an intellectually demanding and exciting opportunity to break through boundaries in research.

Many of the most remarkable advancements in the past 60 years have only been possible through the curiosity and ingenuity of engineers. Our graduates have a consistently strong record of gaining employment with leading companies.

Employers value the skills and experience that enable our graduates to make a positive contribution in their jobs from day one.

Our graduates are employed by companies across the electronics, information technology and communications industries. Recent employers include:
-BAE Systems
-BT
-Philips
-Hewlett Packard
-Logica
-Lucent Technologies
-BBC
-Motorola
-NEC Technologies
-Nokia
-Nortel Networks
-Red Hat

INDUSTRIAL COLLABORATIONS

We draw on our industry experience to inform and enrich our teaching, bringing theoretical subjects to life. Our industrial collaborations include:
-Research and technology transfer projects with industrial partners such as the BBC, Foundry, LionHead and BAE
-A number of our academics offer MSc projects in collaboration with our industrial partners

RESEARCH PERSPECTIVES

This course gives an excellent preparation for continuing onto PhD studies in computer vision related domains.

GLOBAL OPPORTUNITIES

We often give our students the opportunity to acquire international experience during their degrees by taking advantage of our exchange agreements with overseas universities.

In addition to the hugely enjoyable and satisfying experience, time spent abroad adds a distinctive element to your CV.

Read less

This degree mirrors the two-year Masters programme structure that is common in the USA, and is an ideal stepping stone to a PhD or a career in industry.

The optional professional placement component gives you the opportunity to gain experience from working in industry, which cannot normally be offered by the standard technically-focused one-year Masters programme.

PROGRAMME OVERVIEW

The Electronic Engineering Euromasters programme is designed for electronic engineering graduates and professionals with an interest in gaining further qualifications in advanced, cutting-edge techniques and technologies. Current pathways offered include:
-Communications Networks and Software
-RF and Microwave Engineering
-Mobile Communications Systems
-Mobile and Satellite Communications
-Mobile Media Communications
-Computer Vision, Robotics and Machine Learning
-Satellite Communications Engineering
-Electronic Engineering
-Space Engineering
-Nanotechnology and Renewable Energy
-Medical Imaging

Please note that at applicant stage, it is necessary to apply for the Electronic Engineering (Euromasters). If you wish to specialise in one of the other pathways mentioned above, you can adjust your Euromaster programme accordingly on starting the course.

PROGRAMME STRUCTURE

This programme is studied full-time over 24 months and part-time over 60 months. It consists of ten taught modules and an extended project. The following modules are indicative, reflecting the information available at the time of publication. Please note that not all modules described are compulsory and may be subject to teaching availability and/or student demand.
-Digital Communications
-Digital Signal Processing A
-Object Oriented Design and C++
-RF and Microwave Fundamentals
-Nanoscience and Nanotechnology
-Space Dynamics and Missions
-Space Systems Design
-Antennas and Propagation
-Image Processing and Vision
-Fundamentals of Mobile Communications
-Principles of Telecommunications and Packet Networks
-Space Robotics and Autonomy
-Speech and Audio Processing and Recognition
-Satellite Communication Fundamentals
-Satellite Remote Sensing
-Molecular Electronics
-RF Systems and Circuit Design
-Internet of Things
-Nanofabrication and Characterisation
-Space Avionics
-Applied Mathematics for Communication Systems
-Data and Internet Networking
-Digital Design with VHDL
-Computer Vision and Pattern Recognition
-Mediacasting
-Semiconductor Devices and Optoelectronics
-AI and AI Programming
-Advanced Signal Processing
-Advanced Guidance, Navigation and Control
-Image and Video Compression
-Launch Vehicles and Propulsion
-Advanced Mobile Communication Systems
-Microwave Engineering Optional
-Nanoelectronics and Devices
-Network and Service Management and Control
-Operating Systems for Mobile Systems Programming
-Advanced Satellite Communication Techniques
-Nanophotonics Principles and Engineering
-Mobile Applications and Web Services
-Spacecraft Structures and Mechanisms
-Space Environment and Protection
-Renewable Energy Technologies
-Engineering Professional Studies 1 (with industrial Placement)
-Engineering Professional Studies 1
-Engineering Professional Studies 2
-Extended Project

PARTNERS

The MSc Euromasters complies with the structure defined by the Bologna Agreement, and thus it is in harmony with the Masters programme formats adhered to in European universities. Consequently, it facilitates student exchanges with our partner universities in the Erasmus Exchange programme.

A number of bilateral partnerships exist with partner institutions at which students can undertake their project. Current partnerships held by the Department include the following:
-Brno University of Technology, Czech Republic
-University of Prague, Czech Republic
-Universität di Bologna, Italy
-Universität Politècnica de Catalunya, Barcelona, Spain
-Universita' degli Studi di Napoli Federico II, Italy

EDUCATIONAL AIMS OF THE PROGRAMME

The taught postgraduate degree programmes of the Department are intended both to assist with professional career development within the relevant industry and, for a small number of students, to serve as a precursor to academic research.

Our philosophy is to integrate the acquisition of core engineering and scientific knowledge with the development of key practical skills (where relevant). To fulfil these objectives, the programme aims to:
-Attract well-qualified entrants, with a background in electronic engineering, physical sciences, mathematics, computing and communications, from the UK, Europe and overseas
-Provide participants with advanced knowledge, practical skills and understanding applicable to the MSc degree
-Develop participants' understanding of the underlying science, engineering, and technology, and enhance their ability to relate this to industrial practice
-Develop participants' critical and analytical powers so that they can effectively plan and execute individual research/design/development projects
-Provide a high level of flexibility in programme pattern and exit point
-Provide students with an extensive choice of taught modules, in subjects for which the Department has an international and UK research reputation

A graduate from this MSc programme should:
-Know, understand and be able to apply the fundamental mathematical, scientific and engineering facts and principles that underpin electronic engineering
-Be able to analyse problems within the field of electronic engineering and find solutions
-Be able to use relevant workshop and laboratory tools and equipment, and have experience of using relevant task-specific software packages to perform engineering tasks
-Know, understand and be able to use the basic mathematical, scientific and engineering facts and principles associated with the topics within electronic engineering
-Be aware of the societal and environmental context of his/her engineering activities
-Be aware of commercial, industrial and employment-related practices and issues likely to affect his/her engineering activities
-Be able to carry out research-and-development investigations
-Be able to design electronic circuits and electronic/software products and systems

Enhanced capabilities of MSc (Euromasters) graduates:
-Demonstrate transferable skills such as problem solving, analysis and critical interpretation of data, through the undertaking of the extended 90-credit project
-Know how to take into account constraints such as environmental and sustainability limitations, health and safety and risk assessment
-Have gained comprehensive understanding of design processes
-Understand customer and user needs, including aesthetics, ergonomics and usability
-Have acquired experience in producing an innovative design
-Appreciate the need to identify and manage cost drivers
-Have become familiar with the design process and the methodology of evaluating outcomes
-Have acquired knowledge and understanding of management and business practices
-Have gained the ability to evaluate risks, including commercial risks
-Understand current engineering practice and some appreciation of likely developments
-Have gained extensive understanding of a wide range of engineering materials/components
-Understand appropriate codes of practice and industry standards
-Have become aware of quality issues in the discipline

PROGRAMME LEARNING OUTCOMES

The programme provides opportunities for students to develop and demonstrate knowledge and understanding, skills, qualities and other attributes in the following areas:

General transferable skills
-Be able to use computers and basic IT tools effectively
-Be able to retrieve information from written and electronic sources
-Be able to apply critical but constructive thinking to received information
-Be able to study and learn effectively
-Be able to communicate effectively in writing and by oral presentations
-Be able to present quantitative data effectively, using appropriate methods
-Be able to manage own time and resources
-Be able to develop, monitor and update a plan, in the light of changing circumstances
-Be able to reflect on own learning and performance, and plan its development/improvement, as a foundation for life-long learning

Underpinning learning
-Know and understand scientific principles necessary to underpin their education in electronic and electrical engineering, to enable appreciation of its scientific and engineering content, and to support their understanding of historical, current and future developments
-Know and understand the mathematical principles necessary to underpin their education in electronic and electrical engineering and to enable them to apply mathematical methods, tools and notations proficiently in the analysis and solution of engineering problems
-Be able to apply and integrate knowledge and understanding of other engineering disciplines to support study of electronic and electrical engineering

Engineering problem-solving
-Understand electronic and electrical engineering principles and be able to apply them to analyse key engineering processes
-Be able to identify, classify and describe the performance of systems and components through the use of analytical methods and modelling techniques
-Be able to apply mathematical and computer-based models to solve problems in electronic and electrical engineering, and be able to assess the limitations of particular cases
-Use of quantitative methods for problem solving. Be able to apply quantitative methods relevant to electronic and electrical engineering, in order to solve engineering problems
-Understand and be able to apply a systems approach to electronic and electrical engineering problems

Engineering tools
-Have relevant workshop and laboratory skills
-Be able to write simple computer programs, be aware of the nature of microprocessor programming, and be aware of the nature of software design
-Be able to apply computer software packages relevant to electronic and electrical engineering, in order to solve engineering problems

Technical expertise
-Know and understand the facts, concepts, conventions, principles, mathematics and applications of the range of electronic and electrical engineering topics he/she has chosen to study
-Know the characteristics of particular materials, equipment, processes or products
-Have thorough understanding of current practice and limitations, and some appreciation of likely future developments
-Be aware of developing technologies related to electronic and electrical engineering
-Have comprehensive understanding of the scientific principles of electronic engineering and related disciplines
-Have comprehensive knowledge and understanding of mathematical and computer models relevant to electronic and electrical engineering, and an appreciation of their limitations
-Know and understand, at Master's level, the facts, concepts, conventions, principles, mathematics and applications of a range of engineering topics that he/she has chosen to study
-Have extensive knowledge of a wide range of engineering materials and components
-Understand concepts from a range of areas including some from outside engineering, and be able to apply them effectively in engineering projects

Societal and environmental context
-Understand the requirement for engineering activities to promote sustainable development
Be aware of the framework of relevant legal requirements governing engineering activities, including personnel, health, safety and risk (including environmental risk issues
-Understand the need for a high level of professional and ethical conduct in engineering

Employment context
-Know and understand the commercial and economic context of electronic and electrical engineering processes
-Understand the contexts in which engineering knowledge can be applied (e.g. operations and management, technology development, etc.)
-Be aware of the nature of intellectual property
-Understand appropriate codes of practice and industry standards
-Be aware of quality issues
-Be able to apply engineering techniques taking account of a range of commercial and industrial constraints
-Understand the basics of financial accounting procedures relevant to engineering project work
-Be able to make general evaluations of commercial risks through some understanding of the basis of such risks
-Be aware of the framework of relevant legal requirements governing engineering activities, including personnel, health, safety and risk (including environmental risk) issues

Research and development
-Understand the use of technical literature and other information sources
-Be aware of the need, in appropriate cases, for experimentation during scientific investigations and during engineering development
-Be able to use fundamental knowledge to investigate new and emerging technologies
-Be able to extract data pertinent to an unfamiliar problem, and employ this data in solving the problem, using computer-based engineering tools when appropriate
-Be able to work with technical uncertainty

Design
-Understand the nature of the engineering design process
-Investigate and define a problem and identify constraints, including environmental and sustainability limitations, and health and safety and risk assessment issues
-Understand customer and user needs and the importance of considerations such as aesthetics
-Identify and manage cost drivers
-Use creativity to establish innovative solutions
-Ensure fitness for purpose and all aspects of the problem including production, operation, maintenance and disposal
-Manage the design process and evaluate outcomes
-Have wide knowledge and comprehensive understanding of design processes and methodologies and be able to apply and adapt them in unfamiliar situations
-Be able to generate an innovative design for products, systems, components or processes, to fulfil new needs

Project management
-Be able to work as a member of a team
-Be able to exercise leadership in a team
-Be able to work in a multidisciplinary environment
-Know about management techniques that may be used to achieve engineering objectives within the commercial and economic context of engineering processes
-Have extensive knowledge and understanding of management and business practices, and their limitations, and how these may be applied appropriately

GLOBAL OPPORTUNITIES

We often give our students the opportunity to acquire international experience during their degrees by taking advantage of our exchange agreements with overseas universities.

In addition to the hugely enjoyable and satisfying experience, time spent abroad adds a distinctive element to your CV.

Read less

Our MSc in Mobile Media Communications is offered by a department recognised for its internationally-leading research in multimedia signal processing and machine learning.

If you are interested in these fields, and want to receive up-to-date training in emerging technologies, our programme will equip you with the skills and knowledge highly valued by industry.

PROGRAMME OVERVIEW

The delivery of media content relies on many layers of sophisticated signal engineering that can process images, video, speech and audio – and signal processing is at the heart of all multimedia systems.

Our Mobile Media Communications programme explains the algorithms and intricacies surrounding transmission and delivery of audio and video content. Particular emphasis is given to networking and data compression, in addition to the foundations of pattern recognition.

PROGRAMME STRUCTURE

This programme is studied full-time over one academic year and part-time students must study at least two taught technical modules per academic year. It consists of eight taught modules and a standard project. The following modules are indicative, reflecting the information available at the time of publication. Please note that not all modules described are compulsory and may be subject to teaching availability and/or student demand.
-Object Oriented Design and C++
-Image Processing and Vision
-Fundamentals of Mobile Communications
-Speech and Audio Processing and Recognition
-Internet of Things
-EEE3007 Data and Internet Networking
-Computer Vision and Pattern Recognition
-Mediacasting
-AI and AI Programming
-Advanced Signal Processing
-Image and Video Compression
-Advanced Mobile Communication Systems
-Standard Project

EDUCATIONAL AIMS OF THE PROGRAMME

The taught postgraduate Degree Programmes of the Department are intended both to assist with professional career development within the relevant industry and, for a small number of students, to serve as a precursor to academic research.

Our philosophy is to integrate the acquisition of core engineering and scientific knowledge with the development of key practical skills (where relevant).

To fulfil these objectives, the programme aims to:
-Attract well-qualified entrants, with a background in Electronic Engineering, Physical Sciences, Mathematics, Computing & Communications, from the UK, Europe and overseas
-Provide participants with advanced knowledge, practical skills and understanding applicable to the MSc degree
-Develop participants' understanding of the underlying science, engineering, and technology, and enhance their ability to relate this to industrial practice
-Develop participants' critical and analytical powers so that they can effectively plan and execute individual research/design/development projects
-Provide a high level of flexibility in programme pattern and exit point
-Provide students with an extensive choice of taught modules, in subjects for which the Department has an international and UK research reputation

Intended capabilities for MSc graduates:
-Underpinning learning– know, understand and be able to apply the fundamental mathematical, scientific and engineering facts and principles that underpin mobile media communications
-Engineering problem solving - be able to analyse problems within the field of mobile media communications and more broadly in electronic engineering and find solutions
-Engineering tools - be able to use relevant workshop and laboratory tools and equipment, and have experience of using relevant task-specific software packages to perform engineering tasks
-Technical expertise - know, understand and be able to use the basic mathematical, scientific and engineering facts and principles associated with the topics within mobile and media communications
-Societal and environmental context - be aware of the societal and environmental context of his/her engineering activities
-Employment context - be aware of commercial, industrial and employment-related practices and issues likely to affect his/her engineering activities
-Research & development investigations - be able to carry out research-and- development investigations
-Design - where relevant, be able to design electronic circuits and electronic/software products and systems

PROGRAMME LEARNING OUTCOMES

General transferable skills
-Be able to use computers and basic IT tools effectively
-Be able to retrieve information from written and electronic sources
-Be able to apply critical but constructive thinking to received information
-Be able to study and learn effectively
-Be able to communicate effectively in writing and by oral presentations
-Be able to present quantitative data effectively, using appropriate methods
-Be able to manage own time and resources
-Be able to develop, monitor and update a plan, in the light of changing circumstances
-Be able to reflect on own learning and performance, and plan its development/improvement, as a foundation for life-long learning

Underpinning learning
-Know and understand scientific principles necessary to underpin their education in electronic and electrical engineering, to enable appreciation of its scientific and engineering content, and to support their understanding of historical, current and future developments
-Know and understand the mathematical principles necessary to underpin their education in electronic and electrical engineering and to enable them to apply mathematical methods, tools and notations proficiently in the analysis and solution of engineering problems
-Be able to apply and integrate knowledge and understanding of other engineering disciplines to support study of electronic and electrical engineering.

Engineering problem-solving
-Understand electronic and electrical engineering principles and be able to apply them to analyse key engineering processes
-Be able to identify, classify and describe the performance of systems and components through the use of analytical methods and modelling techniques
-Be able to apply mathematical and computer-based models to solve problems in electronic and electrical engineering, and be able to assess the limitations of particular cases
-Be able to apply quantitative methods relevant to electronic and electrical engineering, in order to solve engineering problems
-Understand and be able to apply a systems approach to electronic and electrical engineering problems

Engineering tools
-Have relevant workshop and laboratory skills
-Be able to write simple computer programs, be aware of the nature of microprocessor programming, and be aware of the nature of software design
-Be able to apply computer software packages relevant to electronic and electrical engineering, in order to solve engineering problems

Technical expertise
-Know and understand the facts, concepts, conventions, principles, mathematics and applications of the range of electronic and electrical engineering topics he/she has chosen to study
-Know the characteristics of particular materials, equipment, processes or products
-Have thorough understanding of current practice and limitations, and some appreciation of likely future developments
-Be aware of developing technologies related to electronic and electrical engineering
-Have comprehensive understanding of the scientific principles of electronic engineering and related disciplines
-Have comprehensive knowledge and understanding of mathematical and computer models relevant to electronic and electrical engineering, and an appreciation of their limitations
-Know and understand, at Master's level, the facts, concepts, conventions, principles, mathematics and applications of a range of engineering topics that he/she has chosen to study
-Have extensive knowledge of a wide range of engineering materials and components
-Understand concepts from a range of areas including some from outside engineering, and be able to apply them effectively in engineering projects

Societal and environmental context
-Understand the requirement for engineering activities to promote sustainable development
-Be aware of the framework of relevant legal requirements governing engineering activities, including personnel, health, safety and risk (including environmental risk issues
-Understand the need for a high level of professional and ethical conduct in engineering

Employment context
-Know and understand the commercial and economic context of electronic and electrical engineering processes
-Understand the contexts in which engineering knowledge can be applied (e.g. operations and management, technology development, etc.)
-Be aware of the nature of intellectual property
-Understand appropriate codes of practice and industry standards
-Be aware of quality issues
-Be able to apply engineering techniques taking account of a range of commercial and industrial constraints
-Understand the basics of financial accounting procedures relevant to engineering project work
-Be able to make general evaluations of commercial risks through some understanding of the basis of such risks
-Be aware of the framework of relevant legal requirements governing engineering activities, including personnel, health, safety and risk (including environmental risk) issues

Research and development
-Understand the use of technical literature and other information sources
-Be aware of the need, in appropriate cases, for experimentation during scientific investigations and during engineering development
-Be able to use fundamental knowledge to investigate new and emerging technologies
-Be able to extract data pertinent to an unfamiliar problem, and employ this data in solving the problem, using computer-based engineering tools when appropriate
-Be able to work with technical uncertainty

Design
-Understand the nature of the engineering design process
-Investigate and define a problem and identify constraints, including environmental and sustainability limitations, and health and safety and risk assessment issues
-Understand customer and user needs and the importance of considerations such as aesthetics
-Identify and manage cost drivers
-Use creativity to establish innovative solutions
-Ensure fitness for purpose and all aspects of the problem including production, operation, maintenance and disposal
-Manage the design process and evaluate outcomes
-Have wide knowledge and comprehensive understanding of design processes and methodologies and be able to apply and adapt them in unfamiliar situations
-Be able to generate an innovative design for products, systems, components or processes, to fulfil new needs

Project management
-Be able to work as a member of a team
-Be able to exercise leadership in a team
-Be able to work in a multidisciplinary environment
-Know about management techniques that may be used to achieve engineering objectives within the commercial and economic context of engineering processes
-Have extensive knowledge and understanding of management and business practices, and their limitations, and how these may be applied appropriately

GLOBAL OPPORTUNITIES

We often give our students the opportunity to acquire international experience during their degrees by taking advantage of our exchange agreements with overseas universities.

In addition to the hugely enjoyable and satisfying experience, time spent abroad adds a distinctive element to your CV.

Read less

At the University of Surrey we leads the way in areas such as nanotechnology, vision and signal processing, mobile and wireless communications, multimedia engineering and space and satellite engineering.

PROGRAMME OVERVIEW

Our MSc Euromasters programme is designed for electronic engineering students and professionals with an interest in gaining further qualifications in advanced, cutting-edge techniques and technologies in the selected pathway, with enhanced project, as well as training in transferable skills including business awareness and management.

We offer numerous Electronic Engineering MScs in more specialised fields of study, from space engineering to mobile communications systems, and if you wish to specialise in one of these pathways you can adjust your course accordingly.

The advanced taught technical content is in sub-disciplines of electronic engineering closely aligned with the internationally-leading research conducted in the four research centres of the Department of Electrical and Electronic Engineering.

PROGRAMME STRUCTURE

This programme is studied part-time over 48 months. It consists of eight taught modules and a standard project. Each student will undertake one short course, following which they will be provided with distance learning material in order to study for the subsequent assessment. The students may be assessed for either one or two modules from the short course they undertake.

Typically a student would complete two modules and therefore up to two short courses within the space of year, though they are at liberty to study for more modules if they have the time. The following modules are indicative, reflecting the information available at the time of publication. Please note that not all modules described are compulsory and may be subject to teaching availability and/or student demand.
-Digital Communications
-Digital Signal Processing A
-Object Oriented Design and C++
-RF and Microwave Fundamentals
-IP Networking Protocols and Technologies
-Nanoscience and Nanotechnology
-Space Dynamics and Missions
-Space Systems Design
-Antennas and Propagation
-Image Processing and Vision
-Fundamentals of Mobile Communication
-Principles of Telecommunications and Packet Networks
-Space Robotics and Autonomy
-Speech and Audio Processing and Recognition
-Satellite Communication Fundamentals
-Satellite Remote Sensing
-RF Systems and Circuit Design
-Spacecraft System Design
-Satellite Communications
-Internet of Things
-Space Avionics
-Applied Mathematics for Communication Systems
-Data and Internet Networking
-Digital Design with VDHL
-Computer Vision and Pattern Recognition
-Mediacasting
-Semiconductor Devices and Optoelectronics
-AI and AI Programming
-Advanced Signal Processing
-Advanced Guidance, Navigation and Control
-Image and Video Compression
-Launch Vehicles and Propulsion
-Advanced Mobile Communication Systems
-Microwave Engineering
-Nanoelectronics and Devices
-Operating Systems for Mobile Systems Programming
-Advanced Satellite Communication Techniques
-Nanophotonics Principles and Engineering
-Mobile Applications and Web Services
-Spacecraft Structures and Mechanisms
-Space Environment and Protection
-Renewable Energy Technologies
-60-Credit Standard Project

EDUCATIONAL AIMS OF THE PROGRAMME

The taught postgraduate Degree Programmes of the Department are intended both to assist with professional career development within the relevant industry and, for a small number of students, to serve as a precursor to academic research.

Our philosophy is to integrate the acquisition of core engineering and scientific knowledge with the development of key practical skills (where relevant). To fulfil these objectives, the programme aims to:
-Attract well-qualified entrants, with a background in Electronic Engineering, Physical Sciences, Mathematics, Computing & Communications, from the UK, Europe and overseas
-Provide participants with advanced knowledge, practical skills and understanding applicable to the MSc degree
-Develop participants' understanding of the underlying science, engineering, and technology, and enhance their ability to relate this to industrial practice
-Develop participants' critical and analytical powers so that they can effectively plan and execute individual research/design/development projects
-Provide a high level of flexibility in programme pattern and exit point
-Provide students with an extensive choice of taught modules, in subjects for which the Department has an international and UK research reputation

A graduate from this MSc Programme should:
-Know, understand and be able to apply the fundamental mathematical, scientific and engineering facts and principles that underpin electronic engineering
-Be able to analyse problems within the field of electronic engineering and find solutions
-Be able to use relevant workshop and laboratory tools and equipment, and have experience of using relevant task-specific software packages to perform engineering tasks
-Know, understand and be able to use the basic mathematical, scientific and engineering facts and principles associated with the topics within electronic engineering
-Be aware of the societal and environmental context of his/her engineering activities
-Be aware of commercial, industrial and employment-related practices and issues likely to affect his/her engineering activities
-Be able to carry out research-and-development investigations
-Be able to design electronic circuits and electronic/software products and systems

PROGRAMME LEARNING OUTCOMES

The programme provides opportunities for students to develop and demonstrate knowledge and understanding, skills, qualities and other attributes in the following areas:

General transferable skills
-Be able to use computers and basic IT tools effectively
-Be able to retrieve information from written and electronic sources
-Be able to apply critical but constructive thinking to received information
-Be able to study and learn effectively
-Be able to communicate effectively in writing and by oral presentations
-Be able to present quantitative data effectively, using appropriate methods
-Be able to manage own time and resource
-Be able to develop, monitor and update a plan, in the light of changing circumstances
-Be able to reflect on own learning and performance, and plan its development/improvement, as a foundation for life-long learning

Underpinning learning
-Know and understand scientific principles necessary to underpin their education in electronic and electrical engineering, to enable appreciation of its scientific and engineering content, and to support their understanding of historical, current and future developments
-Know and understand the mathematical principles necessary to underpin their education in electronic and electrical engineering and to enable them to apply mathematical methods, tools and notations proficiently in the analysis and solution of engineering problems
-Be able to apply and integrate knowledge and understanding of other engineering disciplines to support study of electronic and electrical engineering

Engineering problem-solving
-Understand electronic and electrical engineering principles and be able to apply them to analyse key engineering processes
-Be able to identify, classify and describe the performance of systems and components through the use of analytical methods and modelling techniques
-Be able to apply mathematical and computer-based models to solve problems in electronic and electrical engineering, and be able to assess the limitations of particular cases
-Be able to apply quantitative methods relevant to electronic and electrical engineering, in order to solve engineering problems
-Understand and be able to apply a systems approach to electronic and electrical engineering problems

Engineering tools
-Have relevant workshop and laboratory skills
-Be able to write simple computer programs, be aware of the nature of microprocessor programming, and be aware of the nature of software design
-Be able to apply computer software packages relevant to electronic and electrical engineering, in order to solve engineering problems

Technical expertise
-Know and understand the facts, concepts, conventions, principles, mathematics and applications of the range of electronic and electrical engineering topics he/she has chosen to study
-Know the characteristics of particular materials, equipment, processes or products
-Have thorough understanding of current practice and limitations, and some appreciation of likely future developments
-Be aware of developing technologies related to electronic and electrical engineering
-Have comprehensive understanding of the scientific principles of electronic engineering and related disciplines
-Have comprehensive knowledge and understanding of mathematical and computer models relevant to electronic and electrical engineering, and an appreciation of their limitations
-Know and understand, at Master's level, the facts, concepts, conventions, principles, mathematics and applications of a range of engineering topics that he/she has chosen to study
-Have extensive knowledge of a wide range of engineering materials and components
-Understand concepts from a range of areas including some from outside engineering, and be able to apply them effectively in engineering projects

Societal and environmental context
-Understand the requirement for engineering activities to promote sustainable development
-Be aware of the framework of relevant legal requirements governing engineering activities, including personnel, health, safety and risk (including environmental risk issues
-Understand the need for a high level of professional and ethical conduct in engineering

Employment context
-Know and understand the commercial and economic context of electronic and electrical engineering processes
-Understand the contexts in which engineering knowledge can be applied (e.g. operations and management, technology development, etc.)
-Be aware of the nature of intellectual property
-Understand appropriate codes of practice and industry standards
-Be aware of quality issues
-Be able to apply engineering techniques taking account of a range of commercial and industrial constraints
-Understand the basics of financial accounting procedures relevant to engineering project work
-Be able to make general evaluations of commercial risks through some understanding of the basis of such risks
-Be aware of the framework of relevant legal requirements governing engineering activities, including personnel, health, safety and risk (including environmental risk) issues

Research and development
-Understand the use of technical literature and other information sources
-Be aware of the need, in appropriate cases, for experimentation during scientific investigations and during engineering development
-Be able to use fundamental knowledge to investigate new and emerging technologies
-Be able to extract data pertinent to an unfamiliar problem, and employ this data in solving the problem, using computer-based engineering tools when appropriate
-Be able to work with technical uncertainty

Design
-Understand the nature of the engineering design process
-Investigate and define a problem and identify constraints, including environmental and sustainability limitations, and health and safety and risk assessment issues
-Understand customer and user needs and the importance of considerations such as aesthetics
-Identify and manage cost drivers
-Use creativity to establish innovative solutions
-Ensure fitness for purpose and all aspects of the problem including production, operation, maintenance and disposal
-Manage the design process and evaluate outcomes
-Have wide knowledge and comprehensive understanding of design processes and methodologies and be able to apply and adapt them in unfamiliar situations
-Be able to generate an innovative design for products, systems, components or processes, to fulfil new needs

Project management
-Be able to work as a member of a team
-Be able to exercise leadership in a team
-Be able to work in a multidisciplinary environment
-Know about management techniques that may be used to achieve engineering objectives within the commercial and economic context of engineering processes
-Have extensive knowledge and understanding of management and business practices, and their limitations, and how these may be applied appropriately

GLOBAL OPPORTUNITIES

We often give our students the opportunity to acquire international experience during their degrees by taking advantage of our exchange agreements with overseas universities.

In addition to the hugely enjoyable and satisfying experience, time spent abroad adds a distinctive element to your CV.

Read less

• Research-oriented degree provides an exciting opportunity to study in a leading-edge research environment
• The studies combine both theoretical and practical approach
• Specializations in Applied Computing, Artificial Intelligence, and Computer Egineering

The International Master’s Degree Programme in Computer Science and Engineering (CSE) is a two-year research-oriented programme concentrating on intelligent digital solutions to real world problems. During the past decades, Computer Science and Engineering has had a significant impact into our daily lives. The development continues and soon computers will not be used as separate devices anymore. Instead they will blend into our living environments and offer us rich sets of services through natural and intuitive user interfaces. The graduates from Computer Science and Engineering will play a key role in this development.

The two-year programme has three specialisation options:
• Applied Computing
• Artificial Intelligence
• Computer Engineering

Applied Computing focuses on the next generation of interactive systems that place humans at the focus of the technological development. Adopting a multidisciplinary real-world approach, students have to spend a substantial amount of time working in group projects to develop a variety of systems ranging from interactive online services to games and mobile applications, with a strong focus on innovation and design.

Artificial Intelligence focuses in various fields of AI, such as machine learning, machine vision, and data mining. This specialisation provides students with a solid theoretical understanding and practical skills on processing and analyzing digital data and the ability to create intelligent solutions to real world problems with modern AI techniques.

Computer Engineering focuses on both hardware and software aspects of computing with emphasis on embedded system development. In this specialisation, students also study signal processing and its applications, and work with projects on modern signal processors and embedded computers. The specialisation gives the students a good basis to work with Internet of Things (IoT) applications.

In addition to the core specialization options, students can take optional courses to widen their specialization expertise into:
• Biomedical signal analysis
• Machine learning
• Machine vision
• Signal processing
• Embedded systems
• Ubiquitous computing

This Master’s programme is provided by the Faculty of Information Technology and Electrical Engineering, and students are strongly encouraged to work closely with research groups in the faculty that are international leaders in their fields. The Center for Machine Vision and Signal Analysis (CMVS) is renowned world-wide for its 35 years of expertise in computer vision research. The Center for Ubiquitous Computing (UBICOMP) has created a unique research environment for Ubiquitous Computing including multitouch wall-sized displays, smartphone sensing middleware and sensor networks. Biomimetics and Intelligent Systems Group (BISG) is a fusion of expertise from the fields of computer science and biology. During the studies the research groups provide students trainee and master’s thesis positions, with the possibility to continue as a doctoral student, and even as a post-doctoral researcher.

The programme will provide the graduates with sufficient skills to work in a wide variety of positions offered by research institutes and companies mainly operating in the field of information and communications technology (ICT). The graduates are most likely to be employed in research and development related positions, but also management positions and entrepreneurship fit into the profile.

Possible titles include:
• Research Scientist
• Software Engineer
• System Designer
• Project Manager
• Specialist

Students applying for the programme must possess an applicable B.Sc. degree in computer science, electrical engineering or relevant fields such as physics or applied mathematics.

For all enquiries, please refer to our enquiry form: http://www.oulu.fi/university/admissions-contact

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