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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. Read more
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
Vision is the most useful sense we possess and as such accounts for about 30% of the sensing processing of the brain. Read more
Vision is the most useful sense we possess and as such accounts for about 30% of the sensing processing of the brain. The automation of visual processing (ie computer vision) has many applications in the modern world including medical imaging for better diagnosis, surveillance systems to improve security and safety, industrial and domestic robotics plus advanced interfaces for computer games, mobile phones and human-computer interfaces. The possibilities are only limited by our imagination.

Key features
-The unique combination of computer vision and embedded systems skills is highly desirable in state-of-the-art industrial applications.
-This course is accredited by BCS, The Chartered Institute for IT.
-You will have the opportunity to work on your project dissertation in the internationally recognised Digital Imaging Research Centre with groups on visual surveillance, human body motion, medical imaging and robotics and being involved in national and international projects or in collaboration with our industrial contacts.

What will you study?

The Embedded Systems (Computer Vision) pathway will equip you with the knowledge and skills required to specify and build computer vision embedded systems, choosing from different imaging devices and applying software that can process and understand images. You will study a range of option modules encompassing computing, engineering and digital media processing. It may also be possible for you to undertake a real-world project in an industrial placement or as part of high-quality research working alongside DIRC (Digital Imaging Research Centre) groups (eg visual surveillance, human body motion analysis, robotics, medical imaging).

The Embedded Systems (Computer Vision) MSc course can be combined with Management Studies enabling you to develop business and management skills so you can work effectively with business managers to develop innovative and imaginative ways to exploit computer vision and embedded systems for business advantage. This is a key skill for employability, particularly as organisations in the public, private and voluntary sectors grapple with austerity.

Assessment

Coursework and/or exams, research project/dissertation.

Work placement scheme

Kingston University has set up a scheme that allows postgraduate students in the Faculty of Science, Engineering and Computing to include a work placement element in their course starting from September 2017. The placement scheme is available for both international and home/EU students.

-The work placement, up to 12 months; is optional.
-The work placement takes place after postgraduate students have successfully completed the taught portion of their degree.
-The responsibility for finding the placement is with the student. We cannot guarantee the placement, just the opportunity to undertake it.
-As the work placement is an assessed part of the course for international students, this is covered by a student's tier 4 visa.

Details on how to apply will be confirmed shortly.

Course structure

The full MSc course consists of an induction programme, four taught modules, and project dissertation. Please note that this is an indicative list of modules and is not intended as a definitive list.

Embedded Systems (Computer Vision) MSc modules
-Digital Signal Processing
-Real-time Programming
-Artificial Vision Systems
-Project Dissertation
-One option module

Embedded Systems (Computer Vision) with Management Studies MSc modules
-Digital Signal Processing
-Real-time Programming
-Artificial Vision Systems
-Business in Practice
-Project Dissertation

Read less
Vision is the most useful sense we possess and as such accounts for about 30% of the sensing processing of the brain. Read more
Vision is the most useful sense we possess and as such accounts for about 30% of the sensing processing of the brain. The automation of visual processing (ie computer vision) has many applications in the modern world including medical imaging for better diagnosis, surveillance systems to improve security and safety, industrial and domestic robotics plus advanced interfaces for computer games, mobile phones and human-computer interfaces. The possibilities are only limited by our imagination.

Key features
-The unique combination of computer vision and embedded systems skills is highly desirable in state-of-the-art industrial applications.
-This course is accredited by BCS, The Chartered Institute for IT.
-You will have the opportunity to work on your project dissertation in the internationally recognised Digital Imaging Research Centre with groups on visual surveillance, human body motion, medical imaging and robotics and being involved in national and international projects or in collaboration with our industrial contacts.

What will you study?

The Embedded Systems (Computer Vision) pathway will equip you with the knowledge and skills required to specify and build computer vision embedded systems, choosing from different imaging devices and applying software that can process and understand images. You will study a range of option modules encompassing computing, engineering and digital media processing. It may also be possible for you to undertake a real-world project in an industrial placement or as part of high-quality research working alongside DIRC (Digital Imaging Research Centre) groups (eg visual surveillance, human body motion analysis, robotics, medical imaging).
The Embedded Systems (Computer Vision) MSc course can be combined with Management Studies enabling you to develop business and management skills so you can work effectively with business managers to develop innovative and imaginative ways to exploit computer vision and embedded systems for business advantage. This is a key skill for employability, particularly as organisations in the public, private and voluntary sectors grapple with austerity.

Assessment

Coursework and/or exams, research project/dissertation.

Work placement scheme

Kingston University has set up a scheme that allows postgraduate students in the Faculty of Science, Engineering and Computing to include a work placement element in their course starting from September 2017. The placement scheme is available for both international and home/EU students.

-The work placement, up to 12 months; is optional.
-The work placement takes place after postgraduate students have successfully completed the taught portion of their degree.
-The responsibility for finding the placement is with the student. We cannot guarantee the placement, just the opportunity to undertake it.
-As the work placement is an assessed part of the course for international students, this is covered by a student's tier 4 visa.

Details on how to apply will be confirmed shortly.

Course structure

The full MSc course consists of an induction programme, four taught modules, and project dissertation. Please note that this is an indicative list of modules and is not intended as a definitive list.

Embedded Systems (Computer Vision) MSc modules
-Digital Signal Processing
-Real-time Programming
-Artificial Vision Systems
-Project Dissertation
-One option module

Read less
Developed by the Bristol Robotics Laboratory, this Masters gives students unique exposure to world-leading robotics research, real-life automation and computer vision projects, and the opportunity for placements in UK companies to work on topical industry problems. Read more
Developed by the Bristol Robotics Laboratory, this Masters gives students unique exposure to world-leading robotics research, real-life automation and computer vision projects, and the opportunity for placements in UK companies to work on topical industry problems.

The last 20 years have seen a phenomenal growth in the development and application of computer and machine vision technology. With increasingly complex applications across diverse areas, including manufacturing, security and medicine, there is a growing need for professionals who can evaluate, design and implement technically appropriate and economically viable automation systems for enhancing quality and productivity.

The MSc in Automation and Computer Vision at UWE Bristol is one of the very few postgraduate courses that brings together both of these disciplines into one industry-focused, research-informed Masters.

Key benefits

Some students may be able to do an industry placement as part of their dissertation. Projects will be focused on real problems companies are working on. Those that don't go down the industry route will work at UWE Bristol on a topical research problem.

Course detail

The course provides a unique combination of these two overlapping disciplines, with a strong emphasis on robotics hardware for solving 'real-world' problems. You will develop both the technical knowledge and the business skills needed to introduce advanced automation and machine vision techniques in the workplace.

You will also benefit from the University's close links with industry, with guest lectures on many modules and the chance to work on real-life automation and computer vision projects.

Modules

• Automation and Control (30 credits)
• Machine Vision (30 credits)
• Managing finance (15 credits)
• Project management (15 credits)
• Industrial applications (15 credits)
• Industrial case studies (15 credits)

You will also work on an individual project (60 credits), which forms a major part of the course and gives you the chance to work on real-world research or industry projects

Format

Alongside the strong industry-focus of the course, you will have the opportunity to be part of, and work on, projects in the world-leading Bristol Robotics Laboratory, which brings together influential researchers in service robotics, autonomous systems and bio-engineering.

For those already working, we offer this course as a work-based learning course, as well as a standard full or part-time Masters. Employees of relevant industries can attend part of the course to supplement their existing skills or to be assessed on their current skills and knowledge of these highly topical subject areas.

Assessment

We will make use of a range of types of assessment on the course, including written exams, oral assessments and presentations, reports and project work and written assignments.

Careers / Further study

The course is a good grounding for wider careers in engineering, science, information technology, management and medical imaging. For those wishing to pursue further study, the course is also good preparation for a career in academia or research in fields such as computer vision, robotics, medical imaging, or more general engineering, science and information technology.

How to apply

Information on applications can be found at the following link: http://www1.uwe.ac.uk/study/applyingtouwebristol/postgraduateapplications.aspx

Funding

- New Postgraduate Master's loans for 2016/17 academic year –

The government are introducing a master’s loan scheme, whereby master’s students under 60 can access a loan of up to £10,000 as a contribution towards the cost of their study. This is part of the government’s long-term commitment to enhance support for postgraduate study.

Scholarships and other sources of funding are also available.

More information can be found here: http://www1.uwe.ac.uk/students/feesandfunding/fundingandscholarships/postgraduatefunding.aspx

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VIBOT is a two-year International Masters of Excellence in Vision and Robotics sponsored by the European Union under the Erasmus Mundus framework. Read more
VIBOT is a two-year International Masters of Excellence in Vision and Robotics sponsored by the European Union under the Erasmus Mundus framework. Built as collaboration between three leading universities in Europe (Heriot-Watt University in Scotland, the Universitat de Girona in Spain and the Université de Bourgogne in France), it is a truly international degree where students not only learn cutting edge science and engineering but are also exposed to different cultures. Over 50 countries have been represented on the Vibot programs since its inception in 2006.

This is a highly competitive programme aiming at attracting the best European and Overseas students to study robotics and computer vision. A number of very attractive grants (up to €42000) covering the University fees and a stipend for living and travel expenses are offered to the best students in the limit of the available grants (typically 16/year). On average, one in ten student applying is selected for a grant.

In recent years, the amount of digital image information to be stored, processed and distributed has grown dramatically. The generalisation of the use of digital images, in video surveillance, biomedical and e-health systems, and remote sensing, creates new, pressing challenges, and automated management tools are key to enable the organisation, mining and processing of these important knowledge resources. The key subject areas taught are computer vision, pattern recognition and robotics. Research in these areas is very dynamic and relevant to a wide range of sectors, such as the autonomotive industry, autonomous systems, medical imaging and e-health. The course is over two years, students spend the first semester in France, the second in Spain and the third in Scotland. The fourth semester is reserved for Masters thesis.

Career Prospects:
All of our graduates find work in industry or research very quickly and are sought after by research laboratories and leading blue chip companies alike. More and more of our graduates choose an industrial career.

Started in 2006, the VIBOT program has become the leading computer vision and robotics program in Europe. A majority of the VIBOT students have graduated with distinction and around 50% of them continue on to PhD studies.

Links with industry:
Strong links with industry have been established and companies now routinely welcome our students for their final year project. Recently, a 2007-2009 VIBOT student won the BAe Systems Chairman Bronze award for his contribution to autonomous navigation of terrestrial robots, demonstrating that our student are well prepared not only for high academic achievement but also for industry.

Our industrial partners have commented on our program:

“We have hosted VIBOT MSc project for the past 3 years and found them to be of a high calibre - in fact - we hired one of them. Their training seems to equip them well for in medical image analysis research, and what they don't know they quickly learn. The course works them hard - requiring a dissertation, short paper, poster and presentation of their work. This serves us well since it ensures they leave behind a good documentary record in addition to the software output. We look forward to working with VIBOT students in the future.

Ian Poole, PhD.
Scientific Fellow - Image Analysis
Toshiba Medical Visualization Systems Europe, Ltd Bonnington Bond”

“BAE Systems has found the ViBOT students to be of a high calibre and full of enthusiasm. They have all managed to fit into our teams quickly and have made valuable technical contributions. We have hired one student following his placement. We find that, through the students, we can sometimes attempt innovative tasks and try new approaches that are off the critical path of our projects. This can help give us early initial experience of emerging methods or potential applications. The ViBOT students are usually from overseas which has the bonus of adding to the diversity of our student placements, who are typically coming from the UK.

Richard Brimble
Principal Scientist,
BAE SYSTEMS, Advanced Technology Centre,

Facilities:
Our world-class robotics facilities include state of the art robots and 3D scanners. We have several turtlebots (http://www.turtlebot.eu) for land robotics, equipped with state of the art sensing such as the kinect, several human robots (Nao) as well as a wide range of dedicated robots for air and subsea robotics.

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What if your smartphone could recognise that it was you before switching on, and could sense your mood by recognising your facial expressions? What if you… Read more
What if your smartphone could recognise that it was you before switching on, and could sense your mood by recognising your facial expressions? What if you could use a real thumbs-up for 'liking' things on Facebook? How can you play games on an Xbox using only your body gestures? How can you equip cars with in-vehicle technology that could automatically read road signs? These are just some of the fascinating questions that you will strive to answer on this programme.

This programme is intended to respond to a growing skills shortage in research and industry for engineers with a high level of training in the analysis and interpretation of images and video. It covers both low-level image processing and high-level interpretation using state-of-the-art machine learning methodologies. In addition, it offers high-level training in programming languages, tools and methods that are necessary for the design and implementation of practical computer vision systems.

Modules Can Include:
Advanced Transform Methods
Machine Learning
Introduction to Computer Vision
Computer Graphics
Artificial Intelligence
Techniques for Computer Vision
High Performance Computing
C++ for Image Processing
Project

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The Institute of Perception, Action and Behaviour (IPAB) focuses on how to link computational perception, representation, transformation and generation processes to external worlds, in theory and in practice. Read more

Research profile

The Institute of Perception, Action and Behaviour (IPAB) focuses on how to link computational perception, representation, transformation and generation processes to external worlds, in theory and in practice.

This link is vital to areas like bio-mimetic robotics, computer-based generation of external phenomena, such as images, music or actions, and agent-based interaction within computer games and animation.

Supported by the dynamic research culture of IPAB, you can develop robots that learn their own motor control, mimic animal behaviours, or produce autonomous and coordinated team actions.

Or you can work with systems that interpret real images and video, or generate complex behaviour in animated characters.

We aim to link strong theoretical perspectives with practical hands-on construction, and provide the hardware and software support to realise this vision.

Training and support

You carry out your research within a research group under the guidance of a supervisor. You will be expected to attend seminars and meetings of relevant research groups and may also attend lectures that are relevant to your research topic. Periodic reviews of your progress will be conducted to assist with research planning.

A programme of transferable skills courses facilitates broader professional development in a wide range of topics, from writing and presentation skills to entrepreneurship and career strategies.

The School of Informatics holds a Silver Athena SWAN award, in recognition of our commitment to advance the representation of women in science, mathematics, engineering and technology. The School is deploying a range of strategies to help female staff and students of all stages in their careers and we seek regular feedback from our research community on our performance.

Facilities

Our two large robotics labs contain a range of mobile platforms, humanoid robots and custom-built actuation systems that attract continuous interest from funders, industry and members of the public.

Recent developments include the application of robotic hardware to prosthetics and assisted living, and a team that competes in the international robot soccer league.

Our new Edinburgh Centre for Robotics (ECR) brings collaboration with Heriot-Watt University to expand the range of facilities and applications we can explore, and to fund research training.

The machine vision lab has facilities for 3D range data capture, motion capture and high-resolution and high-speed video, and the high performance computing needed for graphics is well supported, including hardware partnerships with companies such as NVIDIA.

Career opportunities

While many of our graduates go on to highly successful academic careers, others find their niche in commercial research labs, putting their knowledge and skills to use in an industry setting.

Several of our recent graduates have set up or joined spin-out robotics companies. Our graphics researchers have strong connections to the media and games industries.

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Computer vision and imaging is the exciting science and technology of machines that see, concerned with building artificial systems that obtain information from images that are derived from a range of sources. Read more
Computer vision and imaging is the exciting science and technology of machines that see, concerned with building artificial systems that obtain information from images that are derived from a range of sources. This MSc in Computing with Vision and Imaging teaches you the skills necessary to undertake work in this ever-evolving field.

Why study at Dundee?

Computer vision and imaging is a rapidly expanding field with plenty of real-life applications and opportunities. Here at Dundee, we encourage a professional, inter-disciplinary and user-centred approach to computer systems design and production.

Application areas include:
controlling processes - e.g. an industrial robot or an autonomous vehicle
detecting events - e.g. for visual surveillance or people counting
organising information - e.g. for indexing databases of images and image sequences
modelling objects or environments - e.g. for industrial inspection
medical image analysis
topographical modelling

You will acquire skills in computer vision, inference, algorithmic underpinnings of computer vision systems, how images and signals are formed, filter, compressed and analysed, and how multiple images can be combined.

Throughout this course, you will also develop the necessary skills to undertake independent research and participate in proposal development and innovation - an excellent grounding for many future careers.

What's Great about studying at Dundee?

Research-led teaching:
Teaching at Dundee is research-led, meaning that the MSc programme benefits from association with cutting-edge research of international standard and its commercial applications.

We also have an active Computer Vision and Image Processing research group. Our Vision and Imaging students are involved in a number of http://www.computing.dundee.ac.uk/projects/vision/projects.php, and have been involved with a number of completed research projects like ACTIVE, a project concerning adaptive interfaces for the operation of secondary controls in motor vehicles using pointing gestures and virtual dashboards.

Links with industry

The School of Computing collaborates with, and has links to, companies such as IBM, NCR and Oracle.

Our facilities

You will have 24-hour access to our award winning and purpose-built Queen Mother Building. It has an unusual mixture of lab space and breakout areas, with a range of conventional and special equipment for you to use. It's also easy to work on your own laptop as there is wireless access throughout the building. Our close ties to industry allows us access to facilities such as Windows Azure and Teradata, and university and industry standard software such as Tableau for you to evaluate and use.

Postgraduate culture

The School of Computing maintains a friendly, intimate and supportive atmosphere, and we take pride in the fact that we know all of our students - you're far more than just a matriculation number to us. We have a thriving postgraduate department with regular seminars and guest speakers.

What you will study

You select seven taught modules, three per semester, during the period September-April. You will make module selections with your advisor.

Semester 1 (Sept-Dec):
Probabilistic Inference and Learning
Signals and Images

Plus two from:
Technology Innovation Management
Computer Graphics
Logical Inference & Symbolic Reasoning
Information Theory

Semester 2 (Jan-Mar):
Vision and Perception
Research Methods

Plus one from:
Computing Research Frontiers
Multi-agent Systems & Grid Computing

Subject to examination performance, you then progress to the MSc project which runs from May to September, or to a Diploma project lasting 9 weeks.

Please note that some of the modules in the programme are shared with other masters programmes and some of the teaching and resources may be shared with our BSc programme. These joint classes offer a valuable opportunity to learn from, and discuss the material with, other groups of students with different backgrounds and perspectives.

How you will be assessed

The taught modules are assessed by continuous assessment plus end of semester examinations in December and March/April. The project is assessed by dissertation.

Computing coursework is often very practical, e.g. writing computer programs, designing interfaces, writing reports, constructing web sites, testing software, implementing databases, analysing problems or presenting solutions to clients.

Careers

The knowledge, skills and understanding that you will gain in the areas of computer vision, inference and learning will enable you to work effectively in the application of video and image-based computing - whether you choose industry, commerce or research.

Computing at the University of Dundee is ranked 21st in the UK according to most recent Times Good University Guide and 12th in the UK according to the Guardian University League Table 2009. The University of Dundee has powered its way to a position as one of Scotland's leading universities with an international reputation for excellence across a range of activities. With over 18,000 students, it is growing fast in both size and reputation. It has performed extremely well in both teaching and research assessment exercises, has spawned a range of spin-out companies to exploit its research and has a model wider-access programme.

Dundee has been described as the largest village in Scotland which gives an indication of how friendly and compact it is. With a population of 150,000 it is not too large but has virtually all the cultural and leisure activities you would expect in a much larger city. It is situated beside a broad estuary of the river Tay, surrounded by hills and farmland, and for lovers of the great outdoors it is hard to imagine another UK location that offers so much all year round on land and water. The University is situated in the centre of Dundee, and everything needed is on the one-stop campus: study facilities, help, advice, leisure activities... yet the attractions of the city centre and the cultural quarter are just a stroll away.

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Take advantage of one of our 100 Master’s Scholarships or College of Science Postgraduate Scholarships to study Data Science at Swansea University, the Times Good University Guide’s Welsh University of the Year 2017. Read more
Take advantage of one of our 100 Master’s Scholarships or College of Science Postgraduate Scholarships to study Data Science at Swansea University, the Times Good University Guide’s Welsh University of the Year 2017. Postgraduate loans are also available to English and Welsh domiciled students. For more information on fees and funding please visit our website.

MSc in Data Science aims to equip students with a solid grounding in data science concepts and technologies for extracting information and constructing knowledge from data. Students of the MSc Data Science will study the computational principles, methods, and systems for a variety of real world applications that require mathematical foundations, programming skills, critical thinking, and ingenuity. Development of research skills will be an essential element of the Data Science programme so that students can bring a critical perspective to current data science discipline and apply this to future developments in a rapidly changing technological environment.

Key Features of the MSc Data Science

The MSc Data Science programme focuses on three core technical themes: data mining, machine learning, and visualisation. Data mining is fundamental to data science and the students will learn how to mine both structured data and unstructured data. Students will gain practical data mining experience and will gain a systematic understanding of the fundamental concepts of analysing complex and heterogeneous data. They will be able to manipulate large heterogeneous datasets, from storage to processing, be able to extract information from large datasets, gain experience of data mining algorithms and techniques, and be able to apply them in real world applications. Machine learning has proven to be an effective and exciting technology for data and it is of high value when it comes to employment. Students of the Data Science programme will learn the fundamentals of both conventional and state-of-the-art machine learning techniques, be able to apply the methods and techniques to synthesise solutions using machine learning, and will have the necessary practical skills to apply their understanding to big data problems. We will train students to explore a variety visualisation concepts and techniques for data analysis. Students will be able to apply important concepts in data visualisation, information visualisation, and visual analytics to support data process and knowledge discovery. The students of the Data Science programme also learn important mathematical concepts and methods required by a data scientist. A specifically designed module that is accessible to students with different background will cover the basics of algebra, optimisation techniques, statistics, and so on. More advanced mathematical concepts are integrated in individual modules where necessary.

The MSc Data Science programme delivers the practical components using a number of programming languages and software packages, such as Hadoop, Python, Matlab, C++, OpenGL, OpenCV, and Spark. Students will also be exposed to a range of closely related subject areas, including pattern recognition, high performance computing, GPU processing, computer vision, human computer interaction, and software validation and verification. The delivery of both core and optional modules leverage on the research strength and capacity in the department. The modules are delivered by lecturers who are actively engaged in world leading researches in this field. Students of the Data Science programme will benefit from state-of-the-art materials and contents, and will work on individual degree projects that can be research-led or application driven.

Modules

Modules for the MSc Data Science programme include:

- Visual Analytics
- Data Science Research Methods and Seminars
- Big Data and Data Mining
- Big Data and Machine Learning
- Mathematical Skills for Data Scientists
- Data Visualization
- Human Computer Interaction
- High Performance Computing in C/C++
- Graphics Processor Programming
- Computer Vision and Pattern Recognition
- Modelling and Verification Techniques
- Operating Systems and Architectures

Facilities

The Department of Computer Science is well equipped for teaching, and is continually upgrading its laboratories to ensure equipment is up-to-date – equipment is never more than three years old, and rarely more than two. Currently, our Computer Science students use three fully networked laboratories: one, running Windows; another running Linux; and a project laboratory, containing specialised equipment. These laboratories support a wide range of software, including the programming languages Java, C# and the .net framework, C, C++, Haskell and Prolog among many; integrated programme development environments such as Visual Studio and Netbeans; the widely-used Microsoft Office package; web access tools; and many special purpose software tools including graphical rendering and image manipulation tools; expert system production tools; concurrent system modelling tools; World Wide Web authoring tools; and databases.

As part of the expansion of the Department of Computer Science, we are building the Computational Foundry on our Bay Campus for computer science and mathematical science.

Career Destinations

- Data Analyst
- Data mining Developer
- Machine Learning Developer
- Visual Analytics Developer
- Visualisation Developer
- Visual Computing Software Developer
- Database Developer
- Data Science Researcher
- Computer Vision Developer
- Medical Computing Developer
- Informatics Developer
- Software Engineer

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The accredited Master of Science program in Computer Science is a two-year program that has been designed for international and German graduate students. Read more
The accredited Master of Science program in Computer Science is a two-year program that has been designed for international and German graduate students. The curriculum is very flexible. Students can compile their individual study plans based on their background and interests. It is also a very practical program. In addition to lectures and tutorials, students will complete two seminars, one or two projects and the master thesis.

In the beginning students will choose one or two key courses. Key courses are courses which introduce the students to the research areas represented at the Department of Computer Science. The following key courses are offered:

• Algorithm Theory
• Pattern Recognition
• Databases and Information Systems
• Software Engineering
• Artificial Intelligence
• Computer Architecture

After that, students can specialize in one of the following three areas:

• Cyber-Physical Systems
• Information Systems
• Cognitive Technical Systems

Here are some examples of subjects offered in the three specialization areas:

Cyber-Physical Systems:

• Cyber-Physical Systems – Discrete Models
• Cyber-Physical Systems – Hybrid Control
• Real Time Operation Systems and Reliability
• Verification of Embedded Systems
• Test and Reliability
• Decision Procedures
• Software Design, Modeling and Analysis in UML
• Formal Methods for Java
• Concurrency: Theory and Practice
• Compiler Construction
• Distributed Systems
• Constraint Satisfaction Problems
• Modal Logic
• Peer-to-Peer Networks
• Program Analysis
• Model Driven Engineering

Information Systems:

• Information Retrieval Data Models and Query Languages
• Peer-to-Peer Networks
• Distributed Storage
• Software Design, Modeling and Analysis in UML
• Security in Large-Scale Distributed Enterprises
• Machine Learning
• Efficient Route Planning
• Bioinformatics I
• Bioinformatics II
• Game Theory
• Knowledge Representation
• Distributed Systems

Cognitive Technical Systems:

• Computer Vision I
• Computer Vision II
• Statistical Pattern Recognition
• Mobile Robotics II
• Simulation in Computer Graphics
• Advanced Computer Graphics
• AI Planning
• Game Theory
• Knowledge Representation
• Constraint Satisfaction Problems
• Modal Logic
• Reinforcement Learning
• Machine Learning
• Mobile Robotics I

We believe that it is important for computer science students to get a basic knowledge in a field in which they might work after graduation. Therefore, our students have the opportunity to complete several courses and/or a project in one of the following application areas:

• Bioinformatics
• Educational Sciences
• Geosciences
• Cognitive Sciences
• Mathematics
• Medicine
• Meteorology
• Microsystems Engineering
• Physics
• Political Sciences
• Psychology
• Sociology
• Economics

In the last semester, students work on their master’s thesis. They are expected to tackle an actual research question in close cooperation with a professor and his/her staff.

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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. Read more
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.

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The fields of graphics, vision and imaging increasingly rely on one another. Read more
The fields of graphics, vision and imaging increasingly rely on one another. This unique and timely MSc provides training in computer graphics, geometry processing, virtual reality, machine vision and imaging technology from world-leading experts, enabling students to specialise in any of these areas and gain a grounding in the others.

Degree information

Graduates will understand the basic mathematical principles underlying the development and application of new techniques in computer graphics and computer vision and will be aware of the range of algorithms and approaches available, and be able to design, develop and evaluate algorithms and methods for new problems, emerging technologies and applications.

Students undertake modules to the value of 180 credits.

The programme consists of four core modules (60 credits), four optional modules (60 credits) and a research project (60 credits).

Core modules
-Mathematical Methods, Algorithmics and Implementation
-Image Processing
-Computer Graphics
-Research Methods

Optional modules
-Machine Vision
-Graphical Models
-Virtual Environments
-Geometry of Images
-Advanced Modelling, Rendering and Animation
-Inverse Problems in Imaging
-Computation Modelling for Biomedical Imaging
-Computational Photography and Capture
-Acquisition and Processing of 3D Geometry

Dissertation/report
All students undertake an independent research project related to a problem of industrial interest or on a topic near the leading edge of research, which culminates in a 60–80 page dissertation.

Teaching and learning
The programme is delivered through a combination of lectures and tutorials. Lectures are often supported by laboratory work with help from demonstrators. Student performance is assessed by unseen written examinations, coursework and a substantial individual project.

Careers

Graduates are ready for employment in a wide range of high-technology companies and will be able to contribute to maintaining and enhancing the UK's position in these important and expanding areas. The MSc provides graduates with the up-to-date technical skills required to support a wealth of research and development opportunities in broad areas of computer science and engineering, such as multimedia applications, medicine, architecture, film animation and computer games. Our market research shows that the leading companies in these areas demand the deep technical knowledge that this programme provides. Graduates have found positions at global companies such as Disney, Sony and Siemens. Others have gone on to PhD programmes at MIT, Princeton University, and Eth Zurich.

Top career destinations for this degree:
-Senior Post-Doctoral Research Associate, University of Oxford
-Software Engineer, Sengtian Software
-Graduate Software Engineer, ARM
-IT Officer, Nalys
-MSc in Computer Games and Entertainment, Goldsmiths, University of London

Employability
UCL Computer Science was one of the top-rated departments in the country, according to the UK Government's most recent research assessment exercise, and our graduates have some of the highest employment rates of any university in the UK. This degree programme also provides a foundation for further PhD study or industrial research.

Why study this degree at UCL?

UCL Computer Science contains some of the world's leading researchers in computer graphics, geometry processing, computer vision and virtual environments.

Research activities include geometric acquisition and 3D fabrication, real-time photo-realistic rendering, mixed and augmented reality, face recognition, content-based image-database search, video-texture modelling, depth perception in stereo vision, colour imaging for industrial inspection, mapping brain function and connectivity and tracking for SLAM (simultaneous localisation and mapping).

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Take advantage of one of our 100 Master’s Scholarships or College of Science Postgraduate Scholarships to study Visual Computing at Swansea University, the Times Good University Guide’s Welsh University of the Year 2017. Read more
Take advantage of one of our 100 Master’s Scholarships or College of Science Postgraduate Scholarships to study Visual Computing at Swansea University, the Times Good University Guide’s Welsh University of the Year 2017. Postgraduate loans are also available to English and Welsh domiciled students. For more information on fees and funding please visit our website.

The MRes Visual Computing is an ideal preparation for following a career of research or specialism within the area of study. In particular the MRes in Visual Computing seeks to prepare you for further research in the areas of Computer Graphics, Computer Vision, Medical Imaging, and Scientific Visualisation.

We seek strongly motivated students who are able to carry out substantial individual study. Such students are likely to want to control their own time, carry out curiosity driven research to an advanced level, and follow self-study material in advanced topics.

You will decide upon your topic of research in discussion with your supervisor in an exciting and recent area of Visual Computing. In collaboration with your supervisor you will evaluate current research and carry your own research programme based on the contribution you will make. The research programme is supported by taught courses covering useful literature and skills.

Course Content

Research Component

The main part of the MRes in Visual Computing is a substantial and challenging project involving cutting edge research. The project is an exciting opportunity for you to carry out research in the area of Visual Computing. You will produce an abstract of your work, a scientific paper, carry out a presentation and produce your final dissertation.

Taught Component

In addition to the research project, you can choose from a range of modules that provide skills and development training in different areas.

Modules available currently include:

Computer Vision and Pattern Recognition (compulsory)
Data Visualisation (compulsory)
Graphics Processor Programming (compulsory)
Research Methodology (compulsory)
Visual Computing Project Development (compulsory)
Distributed Object-Oriented Programming
Interaction Technologies: Information Retrieval
High Performance Computing in C/C++
Interaction Technologies: Hardware and Devices

Facilities

The Department of Computer Science is well equipped for teaching, and is continually upgrading its laboratories to ensure equipment is up-to-date – equipment is never more than three years old, and rarely more than two. Currently, our Computer Science students use three fully networked laboratories: one, running Windows; another running Linux; and a project laboratory, containing specialised equipment. These laboratories support a wide range of software, including the programming languages Java, C# and the .net framework, C, C++, Haskell and Prolog among many; integrated programme development environments such as Visual Studio and Netbeans; the widely-used Microsoft Office package; web access tools; and many special purpose software tools including graphical rendering and image manipulation tools; expert system production tools; concurrent system modelling tools; World Wide Web authoring tools; and databases.

As part of the expansion of the Department of Computer Science, we are building the Computational Foundry on our Bay Campus for computer science and mathematical science.

Careers

All Computer Science courses will provide you the transferable skills and knowledge to help you take advantage of the excellent employment and career development prospects in an ever growing and changing computing and ICT industry.

94% of our Postgraduate Taught Graduates of Computer Science were in professional level work or study [DLHE 14/15]

Research

The results of the Research Excellence Framework (REF) 2014 show that we lead Wales in the field of Computer Science and are in the UK Top 20.

We are ranked 11th in the UK for percentage of world-leading research, and 1st in Wales for research excellence. 40% of our submitted research assessed as world-leading quality (4*).

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This MSc programme offers a broad range of advanced study options, with modules taken from a variety of application areas. It is multidisciplinary and, in addition to computer science, you may choose options in which computer science intersects with other fields. Read more
This MSc programme offers a broad range of advanced study options, with modules taken from a variety of application areas. It is multidisciplinary and, in addition to computer science, you may choose options in which computer science intersects with other fields. The programme prepares you for a wide range of careers depending on your selection of modules studied. Typical jobs after graduation include advanced programmer, software development and support, software engineer, product designer/developer, systems analyst, interface/interaction designer, database developer, and other specialist employment based on your selected study areas.

Programme outline

Modules can include:

Introduction to Computer Vision
XML and Structured Documents
Advanced Program Design
Machine Learning
Design for Human Interaction
Program Specifications
Advanced Database Systems & Technology
Distributed Systems and Security
Introduction to Law for Science and Engineering

Techniques for Computer Vision
The Semantic Web
Information Retrieval
Mobile Services
Security and Authentication
Real Time & Critical Systems
Business Technology Strategy
Interactive Systems Design
Software Analysis and Verification
Software Risk Assessment
C++ for Image Processing


Please note that module availability is subject to change.

Recent graduate destinations

* Support Engineer, Computer Assets
* Analyst, Credit Suisse First Boston
* Business Analyst, Norton Rose
* Queen Mary, University of London
* Tesco Plc
* The Open University

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This programme is designed to equip you with the advanced knowledge and skills to develop the innovative solutions required by today’s rapidly advancing computing industry. Read more
This programme is designed to equip you with the advanced knowledge and skills to develop the innovative solutions required by today’s rapidly advancing computing industry.

Developments in artificial intelligence, computer vision, robotics, mobile technology and games applications have all become a normal part of society’s interaction with computing devices.

This MSc Computer Science provides the opportunity to enhance your existing knowledge of computer programming and mathematical frameworks through laboratory workshops, lectures, debates and independent research.

Working alongside our staff, you will have the chance to develop your critical understanding and gain practical experience in innovative areas such as computer vision and surveillance, robotics and mobile computing in order to develop innovative solutions to current and future challenges.

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