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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.

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This MSc teaches advanced analytical and computational skills for success in a data rich world. Read more
This MSc teaches advanced analytical and computational skills for success in a data rich world. Designed to be both mathematically rigorous and relevant, the programme covers fundamental aspects of machine learning and statistics, with potential options in information retrieval, bioinformatics, quantitative finance, artificial intelligence and machine vision.

Degree information

The programme aims to provide graduates with the foundational principles and the practical experience needed by employers in the area of machine learning and statistics. Graduates of this programme will have had the opportunity to develop their skills by tackling problems related to industrial needs or to leading-edge research.

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). Please note that not all combinations of optional modules will be available due to timetabling restrictions.

Core modules
-Supervised Learning
-Statistical Modelling and Data Analysis
-Graphical Models or Probabilistic and Unsupervised Learning
Plus one of:
-Applied Bayesian Methods
-Statistical Design of Investigations
-Statistical Computing
-Statistical Inference

Optional modules - students select 60 credits from the following list:
-Advanced Topics in Machine Learning
-Affective Computing and Human-Robot Interaction
-Applied Bayesian Methods
-Approximate Inference and Learning in Probabilistic Models
-Computational Modelling for Biomedical Imaging
-Information Retrieval and Data Mining
-Machine Vision
-Selected Topics in Statistics
-Optimisation
-Statistical Design of Investigations
-Statistical Inference
-Statistical Natural Language Programming
-Stochastic Methods in Finance
-Stochastic Methods in Finance 2
-Advanced Topics in Statistics
-Mathematical Programming and Research Methods
-Intelligent Systems in Business

Dissertation/report
All MSc students undertake an independent research project, which culminates in a dissertation of 10,000-12,000 words.

Teaching and learning
The programme is delivered through a combination of lectures, discussions, practical sessions and project work. Student performance is assessed through unseen written examinations, coursework, practical application and the project assessment process.

Careers

There is a strong national and international demand for graduates with skills at the interface of traditional statistics and machine learning. Substantial sectors of UK industry, including leading, large companies already make extensive use of computational statistics and machine learning techniques in the course of their business activities. Globally there are a large number of very successful users of this technology, many located in the UK. Areas in which expertise in statistics and machine learning is in particular demand include; finance, banking, insurance, retail, e-commerce, pharmaceuticals, and computer security. Graduates have gone on to further study at, for example, the Universities of Cambridge, Helsinki, Chicago, as well as at UCL. The MSc is also ideal preparation for a PhD, in statistics, machine learning or a related area.

Top career destinations for this degree:
-Statistical and Algorithm Analyst, Telemetry
-Decision Scientist, Everline
-Computer Vision Researcher, Slyce
-Data Scientist, YouGov
-Research Engineer, DeepMind

Employability
Scientific experiments and companies now routinely generate vast databases and machine learning and statistical methodologies are core to their analysis. There is a considerable shortfall in the number of qualified graduates in this area internationally. CSML graduates have been in high demand for PhD positions across the sciences. In London there are many companies looking to understand their customers better who have hired our CSML graduates. Similarly graduates now work in companies in, amongst others, Germany, Iceland, France and the US in large-scale data analysis. The finance sector has also hired several graduates recently.

Why study this degree at UCL?

The Centre for Computational Statistics and Machine Learning (CSML) is a major European Centre for machine learning having coordinated the PASCAL European Network of Excellence.

Coupled with the internationally renowned Gatsby Computational Neuroscience and Machine Learning Unit, and UCL Statistical Science, this MSc programme draws on world-class research and teaching talents. The centre has excellent links with world-leading companies in internet technology, finance and related information areas.

The programme is designed to train students in both the practical and theoretical sides of machine learning. A significant grounding in computational statistics is also provided.

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The Machine Learning MSc at UCL is a truly unique programme and provides an excellent environment to study the subject. It introduces the computational, mathematical and business views of machine learning to those who want to upgrade their expertise and portfolio of skills in this domain. Read more
The Machine Learning MSc at UCL is a truly unique programme and provides an excellent environment to study the subject. It introduces the computational, mathematical and business views of machine learning to those who want to upgrade their expertise and portfolio of skills in this domain.

Degree information

Students develop an understanding of the principles underlying the development and application of new techniques in this area, alongside an awareness of, and ability to analyse the range and scope of algorithms and approaches available, and design, develop and evaluate appropriate algorithms and methods for new problems and applications.

Students undertake modules to the value of 180 credits. The programme consists of two core modules (30 credits), six optional modules (90 credits) and a research project (60 credits).

Core modules
-Supervised Learning
-Either Graphical Models
OR
-Probabilistic and Unsupervised Learning

Optional modules
-Machine Vision
-Bioinformatics
-Information Retrieval and Data Mining
-Advanced Topics in Machine Learning
-Inverse Problems in Imaging
-Affective Computing and Human-Robot Interaction
-Approximate Inference and Learning in Probabilistic Models
-Applied Machine Learning
-Computational Modelling for Biomedical Imaging
-Programming and Mathematical Methods for Machine Learning
-Statistical Natural Language Programming
-Numerical Optimisation

Dissertation/report
All MSc students undertake an independent research project which culminates in a dissertation ( maximum length of 120 pages) in the form of a project report.

Teaching and learning
The programme is delivered through a combination of lectures, seminars, class discussions and project supervision. Student performance is assessed though a combination of unseen written examination, coursework (much of which involves programming and/or data analysis), practical application, and the research project.

Careers

Graduates from this programme have an excellent employment record. Substantial sectors of UK industry, including leading, large companies already make extensive use of intelligent systems techniques in the course of their business activities, and the UK has a number of very successful developers and suppliers of the technology. Students also benefit from strong corporate and academic connections within the UCL Computer Science alumni network.

Graduates have machine learning research degrees in domains as diverse as robotics, music, psychology, bioinformatics at the universities of Basel, Cambridge, Edinburgh, Nairobi, Oxford and at UCL. Graduates have also found positions with multi national companies such as BAE Systems and BAE Detica.

Top career destinations for this degree:
-Software Engineer, Bisual
-PhD Computer Programming, Newcastle University
-Software Developer, Total Gas & Power
-Risk Analyst, National Bank of Greece
-Research Engineer, Xerox Research Centre India

Employability
Scientific experiments and companies now routinely generate vast databases and machine learning and statistical methodologies are core to their analysis. There is a considerable shortfall in the number of qualified graduates in this area internationally. Machine Learning graduates have been in high demand for PhD positions across the sciences. In London there are many companies looking to understand their customers better who have hired our graduates. Similarly graduates now work in companies in, amongst others, Germany, Iceland, France and the US in large-scale data analysis. The finance sector has also hired several graduates recently.

Why study this degree at UCL?

UCL Computer Science is recognised as a world leader in teaching and research, and our Master's programmes have some of the highest employment rates and starting salaries.

We take an experimental approach to our subject, enjoy the challenge and opportunity of entrepreneurial partnerships and place a high value on our extensive range of industrial collaborations.

This MSc is one of the few leading Master's programmes entirely dedicated to machine learning. It combines a rigorous theoretical academic framework along with specific knowledge of a variety of application fields to fast-track your commercial career or to prepare for PhD research.

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This course is designed to meet the needs of electrical, electrical power, electronic and telecommunication engineers who are looking to open up their career prospects. Read more
This course is designed to meet the needs of electrical, electrical power, electronic and telecommunication engineers who are looking to open up their career prospects. You will specialise in one of three majors: Emerging Power Systems, Telecommunication and Networking, or Embedded Systems. Among a wide range of optional units, you may study electrical power, renewable energy, communications and computer engineering at the system level and the component level.

The course is designed to allow you to undertake further studies in a field of your preference through advanced coursework and a major project, ultimately developing a prototype and presenting a formal thesis on the outcome. With the approval of the course coordinator, you may also include a unit from the Curtin Business School, or the Department of Computing, or the Department of Mathematics and Statistics.

EMERGING POWER SYSTEMS (314675)

Global demands on resources have placed an urgent emphasis on supplying a growing population with affordable, environmentally responsible power. How we manage this challenging paradigm will rely on a new generation of creative, technically savvy engineers. Since fossil fuels are a finite resource, the development of alternative sources of electrical energy such as solar and wind is vital.

The challenges that face you as a power engineer include interfacing renewable sources to the electricity distribution system, maintaining stability in the presence of many small energy sources and guaranteeing an electrical supply in the presence of intermittent sources such as solar power.

This major addresses challenges in the generation, transmission and distribution of electricity. Emergent technologies like smart grid and distributed generation are covered in detail. You will have the opportunity to further investigate and apply emergent technologies through your project work.

TELECOMMUNICATIONS AND NETWORKING (314676)

The electronics and communication fields represent two of the greatest growing technology areas in the world. With the rapid progress of information technology, the role of communications is becoming even more crucial for increasing industry efficiency and competition – whether machine talking to machine, computer with computer or human with human via a wide array of methods.

This major explores relevant topics in telecommunications and networking like mobile radio communications and data network security. The wide range of optional units includes topics such as computer architectural philosophies, LAN and WAN technologies, electromagnetics, error control coding, troubleshooter management, legal frameworks, and system design. You will also have the opportunity to further investigate a specialist area and apply your skills and knowledge through your project work.

EMBEDDED SYSTEMS (314677)

Our world is characterised by the ever-increasing number of intelligent devices which have inbuilt or 'embedded' computers. Computers in the form of microprocessors are being embedded in almost every other form of system to control them or provide additional services, creating a strong demand for electrical engineers in all industrially advanced nations.

In this major, you will study intermediate and advanced topics in embedded systems, for example, embedded systems in field-programmable gate arrays (FPGAs) and embedded software engineering. You will have the opportunity to further investigate and apply emergent technologies in embedded systems through your chosen advanced project.

Credit for previous study

Applications for recognition of prior learning (RPL) are assessed on an individual basis.

2016 Curtin International Scholarships: Merit Scholarship

Curtin University is an inspiring, vibrant, international organisation, committed to making tomorrow better. It is a beacon for innovation, driving advances in technology through high-impact research and offering more than 100 practical, industry-aligned courses connecting to workplaces of tomorrow.

Ranked in the top two per cent of universities worldwide in the Academic Ranking of World Universities 2015, the University is also ranked 25th in the world for universities under the age of 50 in the QS World University Rankings 2015 Curtin also received an overall five-star excellence rating in the QS stars rating.

Curtin University strives to give high achieving international students the opportunity to gain an internationally recognised education through offering the Merit Scholarship. The Merit Scholarship will give you up to 25 per cent of your first year tuition fees and if you enrol in an ELB program at Curtin English before studying at Curtin, you will also receive a 10 per cent discount on your Curtin English fees.

For full details and terms and conditions of this scholarship, please visit: curtin.edu/int-scholarships and click on Merit.

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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.

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. Read more
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. Read more
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
The MS program in Electrical and Electronics Engineering aims to provide advanced education and a cutting edge research experience in electrical and electronics engineering, or in electrical and computer engineering crossing the boundary of the two disciplines. Read more
The MS program in Electrical and Electronics Engineering aims to provide advanced education and a cutting edge research experience in electrical and electronics engineering, or in electrical and computer engineering crossing the boundary of the two disciplines. The focus of this program is excellence in research. Graduates of the program can join industry or continue to work in academia.

Current faculty projects and research interests:

• Micro and Nano Systems (MEMS & NEMS)
• Wireless, Acoustic, Nano and Quantum Communication
• Waves, Optics and Photonics
• Electrical, Biological and Nano-Scale Systems
• Signal, Speech, Image and Video Processing
• Multimedia and Networking
• Machine Learning

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The control and conversion of electric power using solid-state techniques are now commonplace in both the domestic and industrial environments. Read more
The control and conversion of electric power using solid-state techniques are now commonplace in both the domestic and industrial environments. A knowledge and understanding of the diverse disciplines encompassed by Power Electronics: devices, converters, control theory and motor drive systems, is now essential to all power engineers. Power electronics, driven by the need for greater energy efficiency and more accurate control of a wide range of systems, is developing rapidly.

This course aims to provide specialist education in power electronics and drive techniques, covering key fundamental principles along with modern applications and current practices. It provides a specialist education in power electronics and drives techniques, covering key fundamental principles along with modern applications and current practices.

Students will develop:

the analytical and critical powers for the development of hardware and software required for power electronics and drives
the ability to plan and undertake an individual project
interpersonal, communication and professional skills
the ability to communicate ideas effectively in written reports
the technical skills to equip them for a leading career in power electronics or electrical machine drive systems
an understanding of how power electronics are applied within key industries such as aerospace and power supply

Following the successful completion of the taught modules, an individual research project is undertaken during the summer term.

Previous research projects on this course have included:

Development of a microprocessor controlled variable speed permanent magnet motor for an aerospace application
Experimental determination of induction motor torque-speed curves under variable speed
Evaluation of stray reactance in a current source rectifier for marine propulsion motor drives and wind power generators
Design, build and testing of a DSP-controlled switched reluctance motor for an automotive power assisted steering application

Scholarship information can be found at http://www.nottingham.ac.uk/graduateschool/funding/index.aspx

Read less
This MSc programme has been specially designed by the Power Conversion Group to meet the growing demand for electrical engineers who have the knowledge and skills to design integrated electrical systems. Read more
This MSc programme has been specially designed by the Power Conversion Group to meet the growing demand for electrical engineers who have the knowledge and skills to design integrated electrical systems. These systems comprise multiple energy sources, power electronic converters and motor drives, examples include:
Traction, energy storage and power management systems for electric vehicles
Electric actuation, generation and power distribution systems for aircraft
Actively controlled, land-based power distribution systems
Industrial automation schemes

Environmental concerns, the desire to use energy more efficiently and the pressure to reduce operating costs are driving the rapid development and application of these new forms of electrical system. Designers require an understanding of electrical machine fundamentals and power electronics, coupled with a thorough knowledge of control, modelling and system integration techniques.

The individual projects, working with one of the course lectures, are often related to one of our many research projects. So you get to work in our research labs alongside PhD students and research assistants, and benefit from their advice and experience.

Course aims

To develop your ability to integrate strands of power electronics, drives, vehicle systems and small power utilities with the control of these systems.

To enhance your experience through learning in a research-rich environment and through contact with leading researchers in the application of electrical energy conversion technology.

To encourage you to evaluate critically drive and supply technologies applied in manufacturing and transport industries

To enable you to gain experience in analysis and design of systems employing recent developments in research area and to prepare students who wish to continue on to research studies.

Further information about this course can be found on the Power Electronics, Machinesand Drives web pages using the link button.

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This course delivers a broad coverage of all major disciplines in Electrical Power, including power electronics, electric drives, electrical machine design and power systems. Read more

Course Overview

This course delivers a broad coverage of all major disciplines in Electrical Power, including power electronics, electric drives, electrical machine design and power systems. It also covers important electrical power themes such as renewable energy systems and electric vehicles.

The Electrical Power MSc covers the following key subject areas: Electrical Machines; Power Electronics; Electric Drives; Power System Operation; Control of Electrical Power.

A feature of the course is design of electrical systems for transportation and renewable energy applications. This is a particular specialisation of researchers in the School of Electrical and Electronic Engineering.

You will develop a knowledge of industry standard computer aided design and analysis techniques appropriate to electrical power such as the use of software packages such as MagNet, MATLAB, Simulink, PSpice and ERACS.

Throughout the course you use industry standard test and measurement equipment, experimental hardware, and software packages relevant to the field of electrical and power engineering.

The course comprises a mixture of lectures, tutorials, coursework and practical laboratory classes. You will research a specialist topic of your choice through an in-depth project. Innovative educational techniques are designed to equip you with practical design skills and research methodologies.

As a graduate of this course you are equipped with the knowledge and practical experience to embark on a career as an engineer in the field of Electrical Power. You will also have skills in research and knowledge acquisition and a solid foundation for further postgraduate studies in the field of electrical engineering and power engineering.

Modules

For detailed module information see http://www.ncl.ac.uk/postgraduate/courses/degrees/electrical-power-msc/#modules

How to apply

For course application information see http://www.ncl.ac.uk/postgraduate/courses/degrees/electrical-power-msc/#howtoapply

Read less
Our Masters in Electrical and Electronic Engineering is a specialist course designed for engineering graduates to enhance their skills in this area of high technology. Read more
Our Masters in Electrical and Electronic Engineering is a specialist course designed for engineering graduates to enhance their skills in this area of high technology. The ever increasing pace of developments in all areas of electrical and electronic engineering, (and in particular in the systems that are related to energy and the environment), requires engineers with a thorough understanding of operation principles and design methods for various modern electrical and electronic systems. As a graduate you'll be able to not only respond to the latest changes but also to look ahead and help in shaping future developments.

The unique features of this course are that the traditional electrical and electronic engineering subjects are supported by the more modern topics of computer control and machine learning techniques, which are at the forefront of modern electrical and electronic systems in the industry today. This course offers an integrated systems approach to engineering, incorporating modules in advanced power electronics and renewable energy systems, advanced instrumentation and control with signal processing, real-time systems and machine learning techniques.

There is an increasing demand for skilled engineers who are able to design and maintain electrical and electronic systems that are at the forefront of current technologies. These positions cover many industries, hence graduates from this course can expect significantly enhanced job prospects in electrical, electronic as well as systems engineering.

See the website http://www.lsbu.ac.uk/courses/course-finder/electrical-electronic-engineering-msc

Modules

- Digital signal processing
This module introduces the theory behind digital signal processing and how DSP can be implemented in real-time. You will gain an understanding of how to program hardware to perform fundamental DSP algorithms such as filtering and spectral analysis. You will gain a fundamental understanding of DSP algorithms and how to implement them in hardware for real-time applications.

- Pattern recognition and machine learning
This module introduces the fundamentals of both statistical learning theory and practical approaches for solving pattern recognition problems. Further, it consolidates lectures with experimental computer-based assignments to inculcate the basics of machine learning and classification. The module covers the fundamentals of pattern recognition and provides the essential background to machine learning and classification.

- Advanced instrumentation and control
This module develops advanced techniques in data acquisition and manipulation required for instrumentation and control applications. Further, it consolidates lectures with experimental computer-based assignments using industry standard hardware and software (NI DAQ and LabView). The module develops your knowledge and experience in data acquisition and virtual instrumentation used in Industry for control purposes.

- Advanced power electronics and renewable energy systems
The material in this module is divided into two parts. The first part covers the analysis and operation of power electronics and machines and their application in the areas of power conversion, power conditioners and electrical machine drives mostly, found on the 'load' side of the electrical power system but sometimes integrated into the supply network. This part will also include elements of computer control systems that are designed to produce non-sinusoidal waveforms and methods of dealing with undesirable harmonics and their effects on the power network. The second part of the module will focus on renewable energy and sustainability. This will include: solar cells, biomass, wind and wave power; intelligent environmental sensing and feedback (in areas of pollution, petroleum, energy consumption, etc.); and renewable design and effectiveness (solar, wind and wave).

- Technology evaluation and commercialization
In this module you will follow a prescribed algorithm in order to evaluate the business opportunity that can be created from a technology's unique advantages. You will be guided towards identifying a technology project idea that you will evaluate for its business potential. To do this you will conduct detailed research and analysis following a prescribed algorithmic model, in order to evaluate the business potential of this technology idea. The outcomes from this will serve as the basis for implementation of the selected technology in the business sense. Thus you will develop the appropriate commercialisation strategy and write the business plan for their high-tech start-up company.

- Technical, research and professional skills
This module provides training for the skills that are necessary for successful completion of the MSc studies in the near future and for professional development in the long-term future. More specifically, the module teaches how to search and gather relevant technical information, how to extract the essence from a piece of technical literature, how to carry out a critical review of a research paper, how to write a feasibility report, how to give presentations and put your thoughts across effectively, and how to manage a project in terms of time and progress in a group project environment. These are designed to enhance the technical and analytical background that is necessary for the respective MSc stream.

- MSc engineering project
This module requires you to undertake a major project in an area that is relevant to their MSc course. You will chose your project and carry it out under the guidance of your supervisor. At the end of the project, you are required to present a dissertation, which forms a major element of the assessment. The dissertation tests your ability to integrate information from various sources, to conduct an in-depth investigation, to critically analyse results and information obtained and to propose solutions. The other element of the assessment includes an oral presentation. The Individual Project carries 60 credits and is a major part of MSc program.

Employability

The acquired skills in computer control and AI techniques offer additional scope for jobs in the design of decision support systems that cross traditional boundaries between engineering and other disciplines. (i.e. medical, finance). Successful graduates will enjoy exciting career opportunities from a wide range of industries, such as electrical energy supply and control, electronics and instrumentation products and services, intelligent systems and automation to include: automotive, aerospace, electrical and electronic consumer products, telecommunications. The students can also pursue PhD studies after completing the course.

Engineering management skills

Engineering employers have expressed their need for engineers with a solid grasp of the business requirements that underpin real engineering projects. Our course incorporates a management-related module focused on entrepreneurship and project management. This management module develops our graduates' commercial awareness and ensures that they have the skill-set valued by industry employers.

LSBU Employability Services

LSBU is committed to supporting you develop your employability and succeed in getting a job after you have graduated. Your qualification will certainly help, but in a competitive market you also need to work on your employability, and on your career search. Our Employability Service will support you in developing your skills, finding a job, interview techniques, work experience or an internship, and will help you assess what you need to do to get the job you want at the end of your course. LSBU offers a comprehensive Employability Service, with a range of initiatives to complement your studies, including:

- direct engagement from employers who come in to interview and talk to students
- Job Shop and on-campus recruitment agencies to help your job search
- mentoring and work shadowing schemes.

Professional links

The School has a strong culture of research and extensive research links with industry through consultancy works and Knowledge Transfer Partnerships (KTPs). Teaching content on our courses is closely related to the latest research work.

Read less
In the course of the electronic revolution at the end of the 20th century, mechanical engineering was reinvented as the backbone of industrial production. Read more
In the course of the electronic revolution at the end of the 20th century, mechanical engineering was reinvented as the backbone of industrial production. The result is mechatronics, a synergistic combination of mechanical components with electronic and IT systems. This technological integration forms new areas of application like electrical and digital technology in machine communication and control.

With the introduction of the Master program in Mechatronics & Smart Technologies, MCI has filled a gap in the educational offering in the west of Austria. With its international orientation and a consistent focus on practical relevance, the program makes a significant contribution to the goal of establishing the Tyrol as a high-tech location with the ability to compete at the international level and defy the fluctuations of the business cycle. With the implementation of the majors in mechanical and electrical engineering and the specialization in computational mechanics at our partner campus in Paris, MCI continues its way as spear head of the Tyrolean technology offensive.

The goal of the Master program in particular is to equip graduates with a competence in mechatronics that is more than the sum of its parts, i.e. mechanical engineering, electronics and IT. Integration of these three pillars is the key to smart technologies as robotics, automated code generation, multi-physical simulation, systems in systems and smart automation, and their application in electro mobility, industry 4.0 and energy efficiency.

With supporting classes in Leadership, Strategic Management, Marketing and Entrepreneurship, this study program opens up perspectives for knowledge-based careers in the manufacturing and service industries worldwide.

Contents

The Master program in Mechatronics & Smart Technologies lasts four semesters comprising 915 hours of classes.

A semester of the full-time program comprises 15 weeks of lectures. The winter semester starts at the beginning of October until the end of January and the summer semester starts in March and lasts until the end of June.
Classes are entirely taught in English, attendance is required from Monday to Friday with additional block classes as well as project and laboratory work.

For the part-time program, the semesters last 20 weeks, from the beginning of September until the middle of February for the winter semester, and from the end of February until the middle of July for the summer semester. Classes are mainly taught in German but also partly in English. Attendance is required on Fridays from 1.30 to 10 p.m. and on Saturdays from 8 a.m. to 5 p.m., and there are additional block classes as well as project and laboratory work, etc.

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This is an MSc course in Embedded Systems with contributions from the fields of mechatronics and robotics. Embedded systems are microprocessor-based systems within a larger mechanical or electrical system that performs a dedicated function or task. Read more
This is an MSc course in Embedded Systems with contributions from the fields of mechatronics and robotics.

Embedded systems are microprocessor-based systems within a larger mechanical or electrical system that performs a dedicated function or task. They encompass a wide variety of products ranging from small mobile phones to large process automation installations. A practicing engineer in the field of embedded systems needs to have a specialised expertise in more than one of the engineering subjects of this multi-discipline subject.

Our MSc is tailored to provide you with advanced learning in microprocessor systems that are at the heart of embedded systems, with additional contributions from the fields of mechatronics and robotics. This approach reflects the needs of the industry and is well supported by the range in expertise we have in our Department.

The Department of Engineering and Design covers the full gamete of teaching in electronic, telecommunication and computer networks engineering as well as mechanical engineering and product design.

Our academics are a cohesive group of highly skilled lecturers, practitioners and researchers. You'll benefit from your choice of supervisors to support a wide range of modern and multi-discipline Masters-level projects. Our teaching is supported by well-equipped laboratory workshops, using mostly the latest hardware and software available in universities.

- Robot Detectives
LSBU holds an international reputation as a world leader in the use of robotics in non-destructive testing and developing intelligent robotic systems. Groundbreaking projects have ranged from building wall climbing robots to robots that work under water and oil.

See the website http://www.lsbu.ac.uk/courses/course-finder/mechatronics-robotics-engineering-msc

Modules

- Embedded system design
This module shows you how to design and implement an Embedded System on a single IC. You will learn about the basics and the benefits of all programmable devices. The SOC (System on Chip) process flow is explained for FPGAs (Field Programmable Gate Arrays) stressing the role played by the Hardware Description Languages (HDL). The accompanying workshops demonstrate the use of tools and methodologies as well as the programming, verifying and protecting your designs. We use the commercial software Quartus II and QSYS and the hardware development platform DE2 by Altera.

- Individual project
The individual project is a major element of the course. It involves a wider spectrum of multidisciplinary research in design, manufacturing systems, quality management and IT, with due regard to the efficient exploitation of the technology, materials and marketing resources of industrial firms. Students are encouraged to work on industrial-based projects.

- Pattern recognition and machine learning
This module introduces the fundamentals of both statistical learning theory and practical approaches for solving pattern recognition problems. Further, it consolidates lectures with experimental computer-based workshops to inculcate the principles of machine learning and classification. The module covers: Bayesian decision theory, parametric density estimation, linear discriminant functions, perceptrons, support vector machines, neural networks and clustering.

- Microprocessor-based control and robotics
This module will provide information allowing you to critically evaluate and make the right choice of the microprocessor that will be at the heart of your embedded system. To this effect we provide a thorough discussion and qualitative comparison of the various microprocessor architectures and the methods of the software development available to you. The workshop assignments involve interfacing 8 and 32 bit microcontrollers to a wide range of devices, including robotic manipulators and control/measurement instrumentation.

- Electromechanical systems and manufacturing technology
This module consists of two parts. The first part covers the design of electromechanical components of the embedded system. The material presented here derives from the fields of Mechatronics and Robotics. The second part provides information on modern developments in the field of materials and the manufacturing. Examples of topics covered include applications of nano-technology, use of polymers and composites. Manufacturing techniques are described together with process modelling and control that is essential to produce the material to the required specification.

- Technology evaluation and commercialisation
This module includes: research product idea generation; product definition and value proposition; market research and assessment; functional assessment of product concepts; and strategic assessment of commercial viability.

- Technical, research and professional skills
This module includes: an introduction to project management, project planning, research project characteristics, ethics, feasibility analysis of requirements and resources; research methods; stages in project management; modelling and optimisation tools (PERT and CPM); technical report writing.

- Robotics
This module introduces you to the basic elements and principles of modern robotics. You'll gain a thorough theoretical and practical understanding of the fundamental concepts of this important and fast developing field. Essential geometric concepts will be introduced and these will be applied to the analysis and control of several different types of machines. A key feature of the module will be the wide range of robotic devices studied, from industrial serial manipulators, through mobile robots to quadcopters. The workshop for this modules includes various topics such as Robot Programming, Path Planning, Mapping and Localisation.

- MSc project
The individual project is a major element of the course. We offer a supervision of projects from a wide spectrum of either specialized or multi-disciplinary topics. There are opportunities for individual-centered projects as well for the student being allocated specific tasks within a larger research effort. Students are encouraged to work on industrial-based projects under joint supervision with their employer.

Employability

The course has been designed to help to meet the needs of industry. How much your employability will increase, will depend on your background and the personal contribution you make to your development whilst studying on the course.

Benefits for new graduates

If you are a new graduate in electronic or computer engineering then you benefit from the further advanced topics presented. You'll get an opportunity to cut your teeth on a challenging MSc Project, which will demonstrate your abilities to the potential employers. Alternatively, you could also pursue PhD studies after completing the course.

Benefits of returning to University after time working in industry

If you are returning to University after a period of working in industry, then you'll be able to update yourself with the recent technological progress in the field. You'll gain confidence in your ability to perform at your best and stand a better chance to seek challenging work opportunities. If you are already working in the field, the MSc qualification will enhance your status which will may help with your promotion.

Employment links

We are continually developing links with employers who are interested to provide internship to our students . Examples of this can include small VHDL and DSP designs, ARM based designs, industrial design or correlation research. These projects can be performed as part of the curriculum or as part of a research project.

LSBU Employability Services

LSBU is committed to supporting you develop your employability and succeed in getting a job after you have graduated. Your qualification will certainly help, but in a competitive market you also need to work on your employability, and on your career search. Our Employability Service will support you in developing your skills, finding a job, interview techniques, work experience or an internship, and will help you assess what you need to do to get the job you want at the end of your course. LSBU offers a comprehensive Employability Service, with a range of initiatives to complement your studies, including:

- direct engagement from employers who come in to interview and talk to students
- Job Shop and on-campus recruitment agencies to help your job search
- mentoring and work shadowing schemes.

Professional links

The School of Engineering at LSBU has a strong culture of research, extensive research links with industry through consultancy works and Knowledge Transfer Partnerships (KTPs), and teaching content is closely related to the latest research findings in the field.

History and expertise

A strong research tradition and our industrial links has helped shaped the course design, content selection, course delivery and project supervision.

The Department of Engineering and Design has a strong Mechatronics, Robotics and Non-destructive testing research group with a wide national and international profile. This is in addition to excellent research in many areas of mechanical engineering, electrical engineering, product design, computer network and telecommunications engineering.

Read less
In the course of the electronic revolution at the end of the 20th century, mechanical engineering was reinvented as the backbone of industrial production. Read more
In the course of the electronic revolution at the end of the 20th century, mechanical engineering was reinvented as the backbone of industrial production. The result is mechatronics, a synergistic combination of mechanical components with electronic and IT systems. This technological integration forms new areas of application like electrical and digital technology in machine communication and control.

With the introduction of the Master program in Mechatronics & Smart Technologies, MCI has filled a gap in the educational offering in the west of Austria. With its international orientation and a consistent focus on practical relevance, the program makes a significant contribution to the goal of establishing the Tyrol as a high-tech location with the ability to compete at the international level and defy the fluctuations of the business cycle. With the implementation of the majors in mechanical and electrical engineering and the specialization in computational mechanics at our partner campus in Paris, MCI continues its way as spear head of the Tyrolean technology offensive.

The goal of the Master program in particular is to equip graduates with a competence in mechatronics that is more than the sum of its parts, i.e. mechanical engineering, electronics and IT. Integration of these three pillars is the key to smart technologies as robotics, automated code generation, multi-physical simulation, systems in systems and smart automation, and their application in electro mobility, industry 4.0 and energy efficiency.

With supporting classes in Leadership, Strategic Management, Marketing and Entrepreneurship, this study program opens up perspectives for knowledge-based careers in the manufacturing and service industries worldwide.

Major Mechanical Engineering

The specialization in Mechanical Engineering prepares graduates for the challenges of modern mechanical engineering. The focus here is on simulation, hydraulics, pneumatics and material sciences, and also on mechanics, machine dynamics and handling technology.

Contents

The Master program in Mechatronics & Smart Technologies lasts four semesters comprising 915 hours of classes.

A semester of the full-time program comprises 15 weeks of lectures. The winter semester starts at the beginning of October until the end of January and the summer semester starts in March and lasts until the end of June.
Classes are entirely taught in English, attendance is required from Monday to Friday with additional block classes as well as project and laboratory work.

For the part-time program, the semesters last 20 weeks, from the beginning of September until the middle of February for the winter semester, and from the end of February until the middle of July for the summer semester. Classes are mainly taught in German but also partly in English. Attendance is required on Fridays from 1.30 to 10 p.m. and on Saturdays from 8 a.m. to 5 p.m., and there are additional block classes as well as project and laboratory work, etc.

Read less

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