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Taught by experienced research staff from the Centre for Computational Intelligence (CCI), an internationally recognised centre highly rated in the most recent Government Research Assessment Exercise, you gain a professional qualification that gives substantially enhanced career and research prospects in both traditional computing areas and in the expanding area of computational intelligence. Read more

About the course

Taught by experienced research staff from the Centre for Computational Intelligence (CCI), an internationally recognised centre highly rated in the most recent Government Research Assessment Exercise, you gain a professional qualification that gives substantially enhanced career and research prospects in both traditional computing areas and in the expanding area of computational intelligence.

Computational Intelligence encompasses the techniques and methods used to tackle problems not well solved by traditional approaches to computing. The four areas of fuzzy logic, neural networks, evolutionary computing and knowledge based systems encompass much of what is considered to be computational (or artificial) intelligence. There are opportunities to use these techniques in many application areas such as robot control and games development depending on your interests.

Modules include work based on research by the Centre of Computational Intelligence. With an established international reputation, their work focuses on the use of fuzzy logic, artificial neural networks, evolutionary computing, mobile robotics and biomedical informatics, providing theoretically sound solutions to real-world decision making and prediction problems. Past students have published papers with their CCI project supervisors and gone on to PhD study.

Reasons to Study

• Internationally recognised reputation
our internationally recognised Centre of Computational Intelligence (CCI) inputs into the course allowing you to understand the current research issues related to artificial intelligence

• Benefit from our Research Expertise
modules include work-based on research by our Centre for Computational Intelligence (CCI) and focus on the use of fuzzy logic, artificial neural networks, evolutionary computing, mobile robotics and biomedical informatics; providing theoretically sound solutions to real-world decision making and prediction problems

• Flexible study options
full-time, part time or distance learning study options available; making the course suitable for recent graduates and professionals in work

• Dedicated robotics laboratory
have access to our Advanced Mobile Robotics and Intelligent Agents Laboratory. The laboratory contains a variety of mobile robots ranging from the Lego Mindstorms and Pioneers to the Wheelbarrow robot for bomb disposal

• Employment Prospects
artificial Intelligence is a growing industry worldwide, employment opportunities exist in areas such as games development, control systems, software engineering, internet businesses, financial services, mobile communications, programming, and software engineering

Course Structure

Modules

• Computational Intelligence Research Methods
• Artificial Intelligence (AI) Programming
• Mobile Robots
• Fuzzy Logic
• Artificial Neural Networks
• Evolutionary Computing
• Applied Computational Intelligence
• Intelligent Mobile Robots
• Individual Project

Optional placement
We offer a great opportunity to boost your career prospects through an optional one year placement as part of your postgraduate studies. We have a dedicated Placement Unit which will help you obtain this. Once on your placement you will be supported by your Visiting Tutor to ensure that you gain maximum benefit from the experience. Placements begin after the taught component of the course has been completed - usually around June - and last for one year. When you return from your work placement you will begin your project.

Teaching and Assessment

The course consists of an induction unit, eight modules and an individual project. The summer period is devoted to work on the project for full-time students. If you choose to study via distance learning, you would normally take either one module per semester for four years or two modules per semester for four years plus a further year for the project.

Teaching is normally delivered through lectures, seminars, tutorials, workshops, discussions and e-learning packages. Assessment is via coursework only and will usually involve a combination of individual and group work, presentations, essays, reports and projects.

Distance learning material is delivered primarily through our virtual learning environment. Books, DVDs and other learning materials will be sent to you. We aim to replicate the on-site experience as fully as possible by using electronic discussion groups, encouraging contact with tutors through a variety of mediums.

Contact and learning hours

On-site students will have the lessons delivered by the module tutors in slots of three hours. In the full-time route, you can expect to have around 12 hours of timetabled taught sessions each week, with approximately 28 additional hours of independent study. There are also three non-teaching weeks when fulltime students can expect to spend around 40 hours on independent study each week.

To find out more

To learn more about this course and DMU, visit our website:
Postgraduate open days: http://www.dmu.ac.uk/study/postgraduate-study/open-evenings/postgraduate-open-days.aspx

Applying for a postgraduate course:
http://www.dmu.ac.uk/study/postgraduate-study/entry-criteria-and-how-to-apply/entry-criteria-and-how-to-apply.aspx

Funding for postgraduate students
http://www.dmu.ac.uk/study/postgraduate-study/postgraduate-funding-2017-18/postgraduate-funding-2017-18.aspx

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Taught by experienced research staff from the Centre for Computational Intelligence (CCI), an internationally recognised centre highly rated in the most recent Government Research Assessment Exercise, you gain a professional qualification that gives substantially enhanced career and research prospects in both traditional computing areas and in the expanding area of computational intelligence. Read more

About the course

Taught by experienced research staff from the Centre for Computational Intelligence (CCI), an internationally recognised centre highly rated in the most recent Government Research Assessment Exercise, you gain a professional qualification that gives substantially enhanced career and research prospects in both traditional computing areas and in the expanding area of computational intelligence.

Computational Intelligence encompasses the techniques and methods used to tackle problems not well solved by traditional approaches to computing. The four areas of fuzzy logic, neural networks, evolutionary computing and knowledge based systems encompass much of what is considered to be computational (or artificial) intelligence. There are opportunities to use these techniques in many application areas such as robot control and games development depending on your interests.

Modules include work based on research by the Centre of Computational Intelligence. With an established international reputation, their work focuses on the use of fuzzy logic, artificial neural networks, evolutionary computing, mobile robotics and biomedical informatics, providing theoretically sound solutions to real-world decision making and prediction problems. Past students have published papers with their CCI project supervisors and gone on to PhD study.

Reasons to Study

• Internationally recognised reputation
our internationally recognised Centre of Computational Intelligence (CCI) inputs into the course allowing you to understand the current research issues related to artificial intelligence

• Benefit from our Research Expertise
modules include work-based on research by our Centre for Computational Intelligence (CCI) and focus on the use of fuzzy logic, artificial neural networks, evolutionary computing, mobile robotics and biomedical informatics; providing theoretically sound solutions to real-world decision making and prediction problems

• Flexible study options
full-time, part time or distance learning study options available; making the course suitable for recent graduates and professionals in work

• Dedicated robotics laboratory
have access to our Advanced Mobile Robotics and Intelligent Agents Laboratory. The laboratory contains a variety of mobile robots ranging from the Lego Mindstorms and Pioneers to the Wheelbarrow robot for bomb disposal

• Employment Prospects
artificial Intelligence is a growing industry worldwide, employment opportunities exist in areas such as games development, control systems, software engineering, internet businesses, financial services, mobile communications, programming, and software engineering

Course Structure

Modules

• Computational Intelligence Research Methods
• Artificial Intelligence (AI) Programming
• Mobile Robots
• Fuzzy Logic
• Artificial Neural Networks
• Evolutionary Computing
• Applied Computational Intelligence
• Data Mining
• Individual Project

Optional placement
We offer a great opportunity to boost your career prospects through an optional one year placement as part of your postgraduate studies. We have a dedicated Placement Unit which will help you obtain this. Once on your placement you will be supported by your Visiting Tutor to ensure that you gain maximum benefit from the experience. Placements begin after the taught component of the course has been completed - usually around June - and last for one year. When you return from your work placement you will begin your project.

Teaching and Assessment

The course consists of an induction unit, eight modules and an individual project. The summer period is devoted to work on the project for full-time students. If you choose to study via distance learning, you would normally take either one module per semester for four years or two modules per semester for four years plus a further year for the project.

Teaching is normally delivered through lectures, seminars, tutorials, workshops, discussions and e-learning packages. Assessment is via coursework only and will usually involve a combination of individual and group work, presentations, essays, reports and projects.

Distance learning material is delivered primarily through our virtual learning environment. Books, DVDs and other learning materials will be sent to you. We aim to replicate the on-site experience as fully as possible by using electronic discussion groups, encouraging contact with tutors through a variety of mediums.

Contact and learning hours

On-site students will have the lessons delivered by the module tutors in slots of three hours. In the full-time route, you can expect to have around 12 hours of timetabled taught sessions each week, with approximately 28 additional hours of independent study. There are also three non-teaching weeks when fulltime students can expect to spend around 40 hours on independent study each week.

Academic expertise

Taught by experienced research staff from the Centre for Computational Intelligence (CCI), an internationally recognised centre highly rated in the most recent Government Research Assessment Exercise, you will gain a professional qualification that gives substantially enhanced career and research prospects in both traditional computing areas and in the expanding area of computational intelligence.

To find out more

To learn more about this course and DMU, visit our website:
Postgraduate open days: http://www.dmu.ac.uk/study/postgraduate-study/open-evenings/postgraduate-open-days.aspx

Applying for a postgraduate course:
http://www.dmu.ac.uk/study/postgraduate-study/entry-criteria-and-how-to-apply/entry-criteria-and-how-to-apply.aspx

Funding for postgraduate students
http://www.dmu.ac.uk/study/postgraduate-study/postgraduate-funding-2017-18/postgraduate-funding-2017-18.aspx

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

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

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

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

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

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

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

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

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

Our research in this field

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

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

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

Career prospects

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

Job positions

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

Internship

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

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

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Artificial intelligence deals with the theory, design, application, and development of biologically, socially and linguistically motivated computational paradigms. Read more
Artificial intelligence deals with the theory, design, application, and development of biologically, socially and linguistically motivated computational paradigms.

You focus on linking artificial intelligence techniques to real-world applications and projects, including artificial intelligence in business and financial applications, artificial intelligence in games, artificial intelligence in biological sciences and medicine, and artificial intelligence in industrial control.

Our unique course covers the theoretical, applied and practical aspects of artificial intelligence, with an emphasis on:
-Genetic algorithms
-Evolutionary programming
-Fuzzy systems
-Neural networks
-Connectionist systems
-Hybrid intelligent systems

Our School is a community of scholars leading the way in technological research and development. Today’s computer scientists are creative people who are focused and committed, yet restless and experimental. We are home to many of the world’s top scientists, and our work is driven by creativity and imagination as well as technical excellence.

We are ranked Top 10 in the UK in the 2015 Academic Ranking of World Universities, with more than two-thirds of our research rated ‘world-leading’ or ‘internationally excellent (REF 2014).

This course is also available on a part-time basis.

This degree is accredited by the Institution of Engineering and Technology (IET).This accreditation is increasingly sought by employers, and provides the first stage towards eventual professional registration as a Chartered Engineer (CEng).

Our expert staff

Our research covers a range of topics, from materials science and semiconductor device physics, to the theory of computation and the philosophy of computer science, with most of our research groups based around laboratories offering world-class facilities.

Our impressive external research funding stands at over £4 million and we participate in a number of EU initiatives and undertake projects under contract to many outside bodies, including government and industrial organisations.

In recent years we have attracted many highly active research staff and we are conducting world-leading research in areas such as evolutionary computation, brain-computer interfacing, intelligent inhabited environments and financial forecasting.

Specialist facilities

We are one of the largest and best resourced computer science and electronic engineering schools in the UK. Our work is supported by extensive networked computer facilities and software aids, together with a wide range of test and instrumentation equipment.
-We have six laboratories that are exclusively for computer science and electronic engineering students. Three are open 24/7, and you have free access to the labs except when there is a scheduled practical class in progress
-All computers run either Windows 7 or are dual boot with Linux
-Software includes Java, Prolog, C++, Perl, Mysql, Matlab, DB2, Microsoft Office, Visual Studio, and Project
-Students have access to CAD tools and simulators for chip design (Xilinx) and computer networks (OPNET)
-We also have specialist facilities for research into areas including non-invasive brain-computer interfaces, intelligent environments, robotics, optoelectronics, video, RF and MW, printed circuit milling, and semiconductors

Your future

Our course opens up employment opportunities designing intelligent software – in banks and businesses designing prediction systems, in computer games companies designing adaptive games, in pharmaceutical companies designing intelligent systems that model a given drug and its various interactions, and in heavy industries designing control systems.

Our recent graduates have progressed to a variety of senior positions in industry and academia. Some of the companies and organisations where our former graduates are now employed include:
-Electronic Data Systems
-Pfizer Pharmaceuticals
-Bank of Mexico
-Visa International
-Hyperknowledge (Cambridge)
-Hellenic Air Force
-ICSS (Beijing)
-United Microelectronic Corporation (Taiwan)

We also work with the university’s Employability and Careers Centre to help you find out about further work experience, internships, placements, and voluntary opportunities.

Example structure

Postgraduate study is the chance to take your education to the next level. The combination of compulsory and optional modules means our courses help you develop extensive knowledge in your chosen discipline, whilst providing plenty of freedom to pursue your own interests. Our research-led teaching is continually evolving to address the latest challenges and breakthroughs in the field, therefore to ensure your course is as relevant and up-to-date as possible your core module structure may be subject to change.

Artificial Intelligence - MSc
-MSc Project and Dissertation
-Machine Learning and Data Mining
-Professional Practice and Research Methodology
-Group Project
-Intelligent Systems and Robotics
-Computer Vision (optional)
-Game Artificial Intelligence (optional)
-Evolutionary Computation and Genetic Programming (optional)
-Natural Language Engineering (optional)
-Artificial Neural Networks (optional)
-Virtual Worlds (optional)
-Creating and Growing a New Business Venture (optional)
-Learning and Computational Intelligence in Economics and Finance (optional)

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Our MSc Computational Finance equips you with the core concepts and mathematical principles of modern quantitative finance, plus the operational skills to use computational packages (mainly Matlab) for financial modelling. Read more
Our MSc Computational Finance equips you with the core concepts and mathematical principles of modern quantitative finance, plus the operational skills to use computational packages (mainly Matlab) for financial modelling.

We provide practical, hands-on learning about how modern, highly computerised financial markets work, how assets should be priced, and how investors should construct a portfolio of assets. In addition to traditional topics in derivatives and asset pricing, we place a special emphasis on risk management in non-Gaussian environment with extreme events.

You master these areas through studying topics including:
-Non-linear and evolutionary computational methods for derivatives pricing and portfolio management
-Applications of calculus and statistical methods
-Computational intelligence in finance and economics
-Financial markets

You also graduate with an understanding of the use of artificial financial market environments for stress testing, and the design of auctions and other financial contracts.

Our Centre for Computational Finance and Economic Agents is an innovative and laboratory-based teaching and research centre, with an international reputation for leading-edge, interdisciplinary work combining economic and financial modelling with computational implementation.

Our research is geared towards real-world, practical applications, and many of our academic staff have experience of applying their findings in industry and in advising the UK government.

This course is also available on a part-time basis.

Professional accreditation

This degree is accredited by the Institution of Engineering and Technology (IET).This accreditation is increasingly sought by employers, and provides the first stage towards eventual professional registration as a Chartered Engineer (CEng).

Our expert staff

This course is taught by experts with both academic and industrial expertise in the financial and IT sectors. We bring together leading academics in the field from our departments of economics, computer science and business.

Our staff are currently researching the development of real-time trading platforms, new financial econometric models for real-time data, the use of artificially intelligent agents in the study of risk and market-based institutions, operational aspects of financial markets, financial engineering, portfolio and risk management.

Specialist facilities

We are one of the largest and best resourced computer science and electronic engineering schools in the UK. Our work is supported by extensive networked computer facilities and software aids, together with a wide range of test and instrumentation equipment.
-We have six laboratories that are exclusively for computer science and electronic engineering students. Three are open 24/7, and you have free access to the labs except when there is a scheduled practical class in progress
-All computers run either Windows 7 or are dual boot with Linux
-Software includes Java, Prolog, C++, Perl, Mysql, Matlab, DB2, Microsoft Office, Visual Studio, and Project
-Students have access to CAD tools and simulators for chip design (Xilinx) and computer networks (OPNET)
-We also have specialist facilities for research into areas including non-invasive brain-computer interfaces, intelligent environments, robotics, optoelectronics, video, RF and MW, printed circuit milling, and semiconductors

Your future

We have an extensive network of industrial contacts through our City Associates Board and our alumni, while our expert seminar series gives you the opportunity to work with leading figures from industry.

Our recent graduates have gone on to become quantitative analysts, portfolio managers and software engineers at various institutions, including:
-HSBC
-Mitsubishi UFJ Securities
-Old Mutual
-Bank of England

We also work with the university’s Employability and Careers Centre to help you find out about further work experience, internships, placements, and voluntary opportunities.

Example structure

-CCFEA MSc Dissertation
-Financial Engineering and Risk Management
-Introduction to Financial Market Analysis
-Learning and Computational Intelligence in Economics and Finance
-Professional Practice and Research Methodology
-Quantitative Methods in Finance and Trading
-Big-Data for Computational Finance (optional)
-Industry Expert Lectures in Finance (optional)
-Mathematical Research Techniques Using Matlab (optional)
-Programming in Python (optional)
-Artificial Neural Networks (optional)
-High Frequency Finance and Empirical Market Microstructure (optional)
-Machine Learning and Data Mining (optional)
-Trading Global Financial Markets (optional)
-Creating and Growing a New Business Venture (optional)
-Evolutionary Computation and Genetic Programming (optional)
-Constraint Satisfaction for Decision Making (optional)

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The course provides a detailed exposure to the context, issues and methods used to analyse the increasingly complex problems which are found in the defence environment and to support decision making. Read more

Course Description

The course provides a detailed exposure to the context, issues and methods used to analyse the increasingly complex problems which are found in the defence environment and to support decision making. It exposes the types of analysis and allows practical experience of tools and methods which are used, ranging from judgemental analysis through mathematical techniques to models and simulations. The course includes judgemental elicitation and analysis techniques, mathematical analysis methods (including optimisation), war gaming and combat modelling, logistics modelling and simulation methods. The use and utility of all the methods are explored through practical exercises and studies.

Course overview

The modular form of the course, consisting of a compulsory core and a selection of Standard and Advanced modules, enables you to select the course of study most appropriate to your particular requirements.

Standard modules normally comprise a week of teaching (or equivalent for distance learning) followed by a further week of directed study/coursework (or equivalent for part time and distance learning).

Advanced modules, which will enable you to explore some areas in greater depth, are two week (or equivalent for part time and distance learning) individual mini-projects on an agreed topic in that subject, which includes a written report and oral presentation.

- MSc students must complete a taught phase consisting of eight standard modules, which includes two core modules (Introduction to Operational Research Techniques and Decision Analysis), plus four advanced modules, followed by an individual thesis in a relevant topic. Thesis topics will be related to problems of specific interest to students and sponsors or local industry wherever possible.
- PgDip students are required to undertake the same taught phase as the MSc, but without the individual thesis.
- PgCert students must complete the core module (Introduction to Operational Research Techniques) together with five other modules; up to three of these may be advanced modules.

On successful completion of the course you will:

- Demonstrate a thorough understanding of the methods, techniques and tools for modelling defence problems and systems
- Be able to critically assess a range of approaches and methods to help support defence analysis and decision-making.

10 places are normally available for the full-time cohort.

The course is suitable for both military and civilian personnel, including those from defence industry and government departments

Individual Project

An individual research project on an agreed topic that allows you to demonstrate your technical expertise, independent learning abilities and critical appraisal skills.

Modules

Part-time students will typically not study as a cohort, but will follow an agreed individual programme of study, attending courses as convenient.
Advanced Modules, which typically comprise individual self-study, can be selected to follow on from any standard modules that have been chosen.
Standard Modules, which typically involve traditional classroom instruction and/or VLE-based delivery, can be chosen from the following:

Core -

Decision Analysis
Introduction to Operational Research Techniques

Optional -

Advanced Decision Analysis
Advanced Discrete and Continuous Simulation
Advanced Logistics Modelling
Advanced War Gaming and Combat Modelling
Applied Optimisation
Computational Statistics
Discrete and Continuous Simulation
Further Operational Research Techniques
Intelligent Systems
Intelligent Systems - Research Study
Logistics Modelling
Neural Networks
Optimisation
Statistical Analysis and Trials
War Gaming and Combat Modelling
Weapon System Performance Assessment

Assessment

Continuous assessment, written examinations, oral vivas and (MSc only) thesis.
Proportions of different assessment types will vary according to programme and elective options chosen. For an MSc these might typically comprise 15-24% continuous assessment (written and oral), 36-45% written examinations and 40% thesis/dissertation.

Career opportunities

Equips you for:

- Appointments within the armed forces or government, or in the defence related activities of commercial organisations.
- Further research leading to a PhD.

Further Information

For further information on this course, please visit our course webpage - http://www.cranfield.ac.uk/Courses/Masters/Military-Operational-Research

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Computer science is the study of theoretical foundations and practical techniques for implementation in computer systems. Despite its short history, computer science has made major contributions to science and society that have transformed the way we live our lives. Read more
Computer science is the study of theoretical foundations and practical techniques for implementation in computer systems. Despite its short history, computer science has made major contributions to science and society that have transformed the way we live our lives.

There are many sub-fields of computer science and this course provides an opportunity to study a range of these to an advanced level, with a particular emphasis on application development,network security and artificial intelligence.

You will be taught by an internationally recognised team, drawn from the University’s Centre of Excellence in Mobile Applications and Services (CEMAS), the Computer Science and Artificial Intelligence Paradigms research unit (CSAIP) and the Information SecurityResearch Group.

See the website http://courses.southwales.ac.uk/courses/252-msc-computer-science

What you will study

- Real-time Computer Graphics
- Software Development
- Network Security
- Mobile Application Development
- Neural Networks
- Expert Systems
- Professional Skills Development
- Advanced Research Methods
- Project Management
- Research Project: an investigation of your choice, related to the course
- MSc Project: the development and evaluation of a significant application or task of your choice, related to the course.

Learning and teaching methods

The course is delivered in four major blocks that offer an intensive but focused learning pattern, with two entry opportunities for applicants every year – February and September. Full-time students will typically spend 12 hours in classes each week. If you choose to study part-time, this is reduced to around six hours each week. You will study through lectures, tutorials, practical sessions, seminars and projects. You need to spend a significant amount of time working independently, reading and preparing for assessments.

Work Experience and Employment Prospects

The skills developed on this course strongly relate to the role of a software developer in a range of specialised areas. For example, business analytics for optimisation is one of the key areas highlighted by e-skills, and this course provides an opportunity to develop knowledge and skills at the forefront of this field, in addition to practical programming elements.

Students who complete this award will be educated to a professional standard in a range of fields related to computer science, and will have improved transferable skills. These include problem solving, communication, team working, effective use of IT facilities and information retrieval.

With training to Masters level now the recognised professional level of competence, graduates will be better placed to pursue careers in industry, or continue their interest in computer science through research at PhD level.

Assessment methods

You will be assessed primarily by coursework. You will work on a significant research project and major project of your choice, where strong independent thinking, critical analysis and project management skills will be important.

Facilities

We have a full range of high-specification computer labs and an ongoing investment programme to ensure that our facilities stay at the forefront of computing developments.

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This programme has similar high-level outcomes to Advanced Computer Science, while offering the opportunity to focus on topics in Artificial Intelligence, including for example, logic, constraint programming, language processing, machine learning and neural networks. Read more

MSc in Artificial Intelligence

This programme has similar high-level outcomes to Advanced Computer Science, while offering the opportunity to focus on topics in Artificial Intelligence, including for example, logic, constraint programming, language processing, machine learning and neural networks.

In semester 1 students take Artificial Intelligence Principles and Artificial Intelligence Practice, followed by either Constraint Programming or Language and Computation in semester 2. Other modules can be selected from the general MSc portfolio.

All MSc students take a Core Skills module, covering essential academic skills. Students taking the specialist Computer Science or HCI degrees also take an Object-Oriented Programming module, to provide a common practical foundation for coursework in the modules that follow. Students on specialist degree programmes take a number of designated modules appropriate to the particular field. With careful module choice, it is sometimes possible to keep open several different specialist options until the second semester.

During the final three months of the course, you undertake an extended project agreed with staff, culminating in writing a substantial individual dissertation. Students on specialist degrees undertake a project in the chosen area.

Find information on Scholarships here http://www.st-andrews.ac.uk/study/pg/fees-and-funding/scholarships/taught/

Careers

Taught postgraduate degrees in Computer Science produce graduates who are well equipped to pursue careers at the forefront of technology. Our recent graduates have gone on to work in a variety of global, commercial, financial and research institutions, including: Microsoft, Hewlett Packard, Royal Bank of Scotland, Skyscanner, Avaloq, Amadeus, Amazon, Atlas, Avaloq, Barclays, BP, BT, Capricorn Ventis, FactSet, Hailo, Hitachi Data System, Microsoft, OpenBet and Symantec. We also have a number of students who have stayed on to study for a PhD in the School.

Features

* You will be part of a cohort of around 60 taught postgraduate students admitted every year who enjoy many opportunities to work and socialise together.

* You will benefit from the School’s emphasis on excellence in both teaching and research. You will learn and study in our two adjacent purpose-built buildings, in daily contact with our 50+ academic and research staff, as well as undergraduate and research students. Larger lectures take place in nearby science buildings.

* You will experience a wide variety of teaching methods in addition to traditional lectures, with an emphasis on personal and small group teaching.

* You will have 24-hour access to well equipped laboratories, including high-speed wireless Internet access throughout.

* You will have the opportunity to broaden your knowledge beyond your lecture courses by attending the departmental seminar series and distinguished lecture programme and the dedicated Systems and Human Computer Interaction seminar series.

* You will be a part of SICSA, the Scottish Information and Computer Science Alliance, of which St Andrews is a founding partner, giving access to specialised events and training and expert staff at all of Scotland’s universities.

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Cognitive psychology and neuropsychology bring together a range of different theoretical frameworks. This MSc programme provides an overview and critical evaluation of the major issues, investigative strategies, and empirical findings of recent attempts to integrate these different approaches to 'brain cognition'. Read more
Cognitive psychology and neuropsychology bring together a range of different theoretical frameworks. This MSc programme provides an overview and critical evaluation of the major issues, investigative strategies, and empirical findings of recent attempts to integrate these different approaches to 'brain cognition'.

Examine how cognitive psychological, neuropsychological, neurobiological and computer science approaches can be combined to understand how the human mind/brain solves a variety of complex problems, such as recognising objects, remembering previous experiences, reading, speaking and reasoning.

The programme gives you a detailed understanding of the major analytic techniques and research methodologies employed by cognitive psychologists and neuropsychologists. Study a range of general, historical, theoretical and philosophical issues underlying the discipline that will equip you with specialist knowledge and systematic understanding and prepare you for a career in academia or as a practising psychologist.

Visit the website https://www.kent.ac.uk/courses/postgraduate/65/cognitive-psychology-neuropsychology

About the School of Psychology

As a student within the School of Psychology at Kent, you benefit from our supportive, dynamic and diverse environment for creative research and learning.

All of our taught Master’s (MSc) programmes have been recognised by the UK Economic and Social Research Council (ESRC) as meeting the nationally recognised criteria for preparation training for PhD research.

Conducting both basic and applied research in several areas, Psychology at Kent is highly regarded as a leading European centre for postgraduate research. Our long-established international reputation in social psychology is complemented by our strengths in cognitive, developmental and forensic psychology. We attract excellent visiting scholars and postgraduate students from both within the UK and overseas.

Some of our PhD students are self-funded, and others are funded by grants or awards either from the School, UK or their countries of origin. Some are also paid to undertake part-time teaching within the School. We have a strong track record of attracting ESRC research studentship funding, which involves partnerships with external organisations such as Age UK and the Equality and Human Rights Commission and collaborative studentships with partners such as People United.

Modules

The modules below are indicative of those offered on this programme. This list is based on the current curriculum and may change year to year in response to new curriculum developments and innovation.

SP801 - Statistics and Methodology (40 credits)
SP827 - Current Issues in Cognitive Psychology and Neuropsychology (40 credits)
SP998 - Advanced Research Project in Psychology (60 credits)
SP846 - Cognitive Neural Networks (20 credits)
SP850 - Advanced Cognitive (Neuroscience) Methods in Practice (20 credits)
SP851 - Advanced Topics in Cognitive Development (20 credits)
SP853 - The Psychology of Eyewitness Testimony (20 credits)
SP854 - Advanced Topics in Developmental Psychopathology (20 credits)
SP829 - Advanced Topics in Cognition in Action (20 credits)

Assessment

The programme mainly involves lecture and seminar based teaching. In addition, particular option units (such as computational modelling) require 'hands-on' experience and learning of particular skills. Staff contact time is eight hours per week. You are expected to study for 1,800 hours over 45 weeks.

Assessment is mainly by coursework assignment (4-6,000 word essays), examination (for the Advanced Statistics and Methodology module only), plus the dissertation.

Programme aims

This programme aims to:

- foster your intellectual development by providing you with specialised knowledge of a range of theoretical approaches to cognitive psychology/neuropsychology and statistical and methodological expertise in order that you should be well equipped to make your own original contribution to psychological knowledge

- provide teaching that is informed by current research and scholarship and that requires you to engage with aspects of work at the frontiers of knowledge

- help you to develop research skills and transferable skills in preparation for entering academic or other careers as psychologists
satisfy the academic requirements of the knowledge base specified by the British Psychological Society

- enable you to manage your own learning and to carry out independent research

- help you to develop general critical, analytic and problem-solving skills that can be applied in a wide range of settings.

Research themes

The School of Psychology is highly regarded as a leading European centre for postgraduate research, with an international reputation for excellence in social psychology (including group processes and intergroup relations); cognition and neuroscience; developmental psychology; and forensic psychology. We have staff who can supervise research degrees in all of these areas. The research environment is designed to sustain a strong, vibrant research culture, encourage collaboration, and unite staff and students with shared research interests. Our themes ensure critical mass and create a highly energetic and stimulating intellectual climate.

Research activity is supported by:

- centrally co-ordinated provision and use of laboratories and technical support

- selection of speakers for our weekly departmental research colloquia

- weekly research meetings within each theme

- developing, reporting and analysing research, and hosting our many visiting scholars

- several monthly small meeting series on specific areas of cross-cutting research (such as forensic, social development, emotion, social cognition and health).

Careers

Our postgraduate students commonly go into the fields of health, teaching or further education. For instance, many of our graduates take up roles as assistant psychologists in the NHS with a view to becoming a professional clinical or forensic psychologist. Upon completing our Master’s courses, graduates have also pursued doctoral study and academic careers at higher education institutions.

The programmes we offer help you to develop general critical, analytic and problem-solving skills that can be applied in a wide range of settings.

Professional recognition

All of our taught Master’s (MSc) programmes have been recognised by the UK Economic and Social Research Council (ESRC) as meeting the nationally recognised criteria for preparation training for PhD research.

Find out how to apply here - https://www.kent.ac.uk/courses/postgraduate/how-to-apply/

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Gas Turbine Technology provides a comprehensive background in the design and operation of different types of gas turbines for all applications. Read more

Course Description

Gas Turbine Technology provides a comprehensive background in the design and operation of different types of gas turbines for all applications. This course is designed for those seeking a career in the design, development, operations and maintenance of power and propulsion systems. Graduates are provided with the skills that allow them to deliver immediate benefits in a very demanding and rewarding workplace and therefore are in great demand. The course is suitable for graduates seeking a challenging and rewarding career in an international growth industry.

The UK continues to lead the world in power and propulsion technology. In addition to its established aerospace role, the gas turbine is finding increasing application in power generation, oil and gas pumping, chemical processing and power plants for ships and other large vehicles.

Course overview

The course consists of approximately ten to fifteen taught modules and an individual research project.

In addition to management, communication, team work and research skills, each student will attain at least the following outcomes from this degree course:

- Provide the skills required for a rewarding career in the field of propulsion and power.
- Meet employer requirements for graduates within power and propulsion industries.
- Demonstrate a working knowledge and critical awareness of gas turbine performance, analysis techniques, component design and associated technologies.
- Explain, differentiate and critically discuss the underpinning concepts and theories for a wide range of areas of gas turbine engineering and associated applications.
- Be able to discern, select and apply appropriate analysis techniques in the assessment of particular aspects of gas turbine engineering.

Individual Project

You are required to submit a written thesis describing an individual research project carried out during the course. Many individual research projects have been carried out with industrial sponsorship, and have often resulted in publication in international journals and symposium papers. This thesis is examined orally in September in the presence of an external examiner.

Recent Individual Research Projects include:

- S-duct aerodynamic shape multi-objective optimisation
- Performance modelling of evaporative gas turbine cycles for marine applications
- Mechanical integrity/stress analysis of the high pressure compressor of a new engine
- High pressure turbine blade life analysis for a civilian derivative aircraft conducting military operations
- Engine performance degradation due to foulants in the environment
- Effects of manufacturing tolerances on gas turbine performance and components
- Development of a transient combustion model
- Numerical fan modelling and aerodynamic analysis of a high bp ratio turbofan engine
- Combustor modelling
- Impact of water ingestion on large jet engine performance and emissions
- Windmilling compressor and fan aerodynamics
- Neural networks based sensor fault diagnostics for industrial gas turbine engines
- Boundary layer ingestion for novel aircraft
- Multidisciplinary design optimisation for axial compressors
- Non-linear off design performance adaptation for a twin spool turbofan engine
- Engine degradation analysis and washing effect on performance using measured data.

Modules

The taught programme for the Gas Turbine Technology masters consists of seven compulsory modules and up to seven optional modules. The modules are generally delivered from October to April.

Core -

Blade Cooling
Combustors
Engine Systems
Gas Turbine Theory and Performance
Mechanical Design of Turbomachinery
Gas Turbine Simulation and Diagnostics
Turbomachinery

Optional -

Computational Fluid Dynamics
Fatigue and Fracture
Gas Turbine Applications
Jet Engine Control (only October intake)
Management for Technology
Propulsion Systems Performance and Integration
Rotating Equipment Selection

Assessment

The final assessment is based on two components of equal weight; the taught modules (50%) and the individual research project (50%). Assessment is by examinations, assignments, presentations and thesis.

Funding

A variety of funding, including industrial sponsorship, is available. Please contact us for details.

Cranfield Postgraduate Loan Scheme (CPLS) - https://www.cranfield.ac.uk/Study/Postgraduate-degrees/Fees-and-funding/Funding-opportunities/cpls/Cranfield-Postgraduate-Loan-Scheme

The Cranfield Postgraduate Loan Scheme (CPLS) is a funding programme providing affordable tuition fee and maintenance loans for full-time UK/EU students studying technology-based MSc courses.

Career opportunities

- Gas turbine engine manufacturers
- Airframe manufacturers
- Airline operators
- Regulatory bodies
- Aerospace/Energy consultancies
- Power production industries
- Academia: doctoral studies.

Further Information

For further information on this course, please visit our course webpage - http://www.cranfield.ac.uk/Courses/Masters/Gas-Turbine-Technology-option-Thermal-power

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The course addresses the design, development, procurement, use and management of models and simulations for applications in experimentation, training, testing, analysis and assessment of military forces, systems and equipment. Read more

Course Description

The course addresses the design, development, procurement, use and management of models and simulations for applications in experimentation, training, testing, analysis and assessment of military forces, systems and equipment.

Overview

On successful completion of the course you will be familiar with the technologies, methodologies, principles and terminology of Modelling and Simulation as used across defence, including the challenges and issues as well as the benefits. Through use of facilities such as the Simulation and Synthetic Environment Laboratory (SSEL), with its wide range of specialist applications, students will gain a broad understanding of modelling and simulation in areas such as training, acquisition, decision-support, analysis and experimentation.

•10 places are normally available for the full-time cohort
•The course is suitable for both military and civilian personnel, including those from defence industry and government departments

Start date: Full-time: annually in September. Part-time: by arrangement

Duration: Full-time MSc - one year, Part-time MSc - up to three years, Full-time PgCert - one year, Part-time PgCert - two years, Full-time PgDip - one year, Part-time PgDip - two years

English Language Requirements

Students whose first language is not English must attain an IELTS score of 6.5.

Course overview

The modular form of the course, consisting of a compulsory core and a selection of standard and advanced modules, enables each student to select the course of study most appropriate to their particular requirements.

Standard modules normally comprise a week of teaching (or equivalent for distance learning) followed by a further week of directed study/coursework (or equivalent for part time and distance learning).

Advanced modules, which enable students to explore some areas in greater depth, are two week (or equivalent for part time and distance learning) individual mini-projects on an agreed topic in that subject, which includes a written report and oral presentation.

- MSc students must complete a taught phase consisting of eight standard modules, which includes two core modules (Foundations of Modelling and Simulation and Networked and Distributed Simulation), plus four advanced modules, followed by an individual thesis in a relevant topic. Thesis topics will be related to problems of specific interest to students and sponsors of local industry wherever possible.

- PgDip students are required to undertake the same taught phase as the MSc, but without the individual thesis.

- PgCert students must complete the core module (Foundations of Modelling and Simulation) together with five other modules; up to three of these may be advanced modules.

Modules

Part-time students will typically not study as a cohort, but will follow an agreed individual programme of study, attending courses as convenient.
Advanced Modules, which typically comprise individual self-study, can be selected to follow on from any standard modules that have been chosen.
Standard Modules, which typically involve traditional classroom instruction and/or VLE-based delivery, can be chosen from the following:

Core:
- Foundations of Modelling and Simulation
- Networked and Distributed Simulation

Elective:
- Advanced Computer Graphics
- Advanced Discrete and Continuous Simulation
- Advanced Logistics Modelling
- Advanced Modelling and Simulation
- Advanced War Gaming and Combat Modelling
- Computational Statistics
- Computer Graphics
- Discrete and Continuous Simulation
- High Performance and Parallel Computing
- Intelligent Systems
- Intelligent Systems - Research Study
- Logistics Modelling
- Networked and Distributed Simulation Exercise
- Neural Networks
- Programming and Software Development in C
- Statistical Analysis and Trials
- War Gaming and Combat Modelling
- Weapon System Performance Assessment

Individual Project

An individual research project on an agreed topic that allows you to demonstrate your technical expertise, independent learning abilities and critical appraisal skills.

Assessment

Continuous assessment, written examinations, oral vivas and (MSc only) thesis.

Proportions of different assessment types will vary according to programme and modules taken. For an MSc these might typically comprise 15-24% continuous assessment (written and oral), 36-45% written examinations and 40% thesis/dissertation.

Career opportunities

Equips you for simulation-specific appointments within the armed forces or government, or in the defence related activities of commercial organisations.

For further information

On this course, please visit our course webpage http://www.cranfield.ac.uk/Courses/Masters/Defence-Simulation-and-Modelling

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Course formats. All of our taught MSc courses are available in several formats. - 12-month intensive MSc for graduates with a good Honours degree. Read more
Course formats

All of our taught MSc courses are available in several formats:

- 12-month intensive MSc for graduates with a good Honours degree
- 2-year International Masters for overseas students with an ordinary Bachelors degree
- With an optional industrial placement (8-50 weeks of paid work experience)
- Part-time over 3 years

Course overview

This conversion course prepares graduates from any discipline for a career in, or involving, computing. No prior knowledge of computer science is required. A broad introduction is provided, including the key technologies and skills needed for employment. You can explore your personal interests through a variety of optional modules. Advanced intellectual, teamwork, communication and other transferable skills are developed.

Hundreds of past graduates from this course are now working across the globe for companies such as IBM, Cisco, Logica/CMG, Pfizer, Reuters, Shell and Zurich Financial. Some chose technical careers in leading software houses, advanced technology companies or commercial sectors. Others work at the interface between technicians and clients, as systems analysts or consultants. Many now hold senior positions as project leaders or managers. You might like to follow in their footsteps.

Funding is available for well-qualified students of any nationality.

Further details: http://www.cs.kent.ac.uk/teaching/pg/

Course content (Honours degree entry; see above web page for details of Ordinary degree entry)

If you have not studied programming before, or only a little (introductory stream)

- Introduction to Object-Oriented Programming (Java)
- Advanced Object-Oriented Programming (Java)

If you have a good working knowledge of programming (advanced stream)

- Advanced Java for Programmers

Other core modules for all students:

- Software Engineering
- Web-based Information System Development
- Systems Architecture
- Logic and Logic Programming
- Project Research
- Project and Dissertation

Optional modules available to all students (choose 1):

- Advanced English for Academic Study
- Computer Graphics and Animation
- Contracts, Professional Responsibility and Computing Law
- Data Mining and Knowledge Discovery
- Introduction to Intelligent Systems
- Mobile and Ubiquitous Computing

Additional options for advanced stream only (choose 1 more):

- C++ Programming
- Cognitive Neural Networks
- Human-Computer Interaction
- IT Consultancy Methods
- IT Consultancy Practice (includes work experience)
- Networks and Network Security

Optional industrial placement (8-50 weeks of paid work experience).

The options available may vary from year to year and are subject to timetabling and prerequisite constraints.
Advanced English for Academic Study may be compulsory for non-native speakers who need additional support.

Further details: http://www.cs.kent.ac.uk/teaching/pg/

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The School of Engineering and Digital Arts offers research-led degrees in a wide range of research disciplines, related to Electronic, Control and Information Engineering, in a highly stimulating academic environment. Read more
The School of Engineering and Digital Arts offers research-led degrees in a wide range of research disciplines, related to Electronic, Control and Information Engineering, in a highly stimulating academic environment. The School enjoys an international reputation for its work and prides itself in allowing students the freedom to realise their maximum potential.

Established over 40 years ago, the School has developed a top-quality teaching and research base, receiving excellent ratings in both research and teaching assessments.

We undertake high-quality research that has had significant national and international impact, and our spread of expertise allows us to respond rapidly to new developments. Our 30 academic staff and over 130 postgraduate students and research staff provide an ideal focus to effectively support a high level of research activity. There is a thriving student population studying for postgraduate degrees in a friendly and supportive teaching and research environment.

We have research funding from the Research Councils UK, European research programmes, a number of industrial and commercial companies and government agencies including the Ministry of Defence. Our Electronic Systems Design Centre and Digital Media Hub provide training and consultancy for a wide range of companies. Many of our research projects are collaborative, and we have well-developed links with institutions worldwide.

Visit the website https://www.kent.ac.uk/courses/postgraduate/262/electronic-engineering

Project opportunities

Some projects available for postgraduate research degrees (http://www.eda.kent.ac.uk/postgraduate/projects_funding/pgr_projects.aspx).

Research areas

- Communications

The Group’s activities cover system and component technologies from microwave to terahertz frequencies. These include photonics, antennae and wireless components for a broad range of communication systems. The Group has extensive software research tools together with antenna anechoic chambers, network and spectrum analysers to millimetre wave frequencies and optical signal generation, processing and measurement facilities. Current research themes include:

- photonic components
- networks/wireless systems
- microwave and millimetre-wave systems
- antenna systems
- radio-over-fibre systems
- electromagnetic bandgaps and metamaterials
- frequency selective surfaces.

- Intelligent Interactions:

The Intelligent Interactions group has interests in all aspects of information engineering and human-machine interactions. It was formed in 2014 by the merger of the Image and Information Research Group and the Digital Media Research Group.

The group has an international reputation for its work in a number of key application areas. These include: image processing and vision, pattern recognition, interaction design, social, ubiquitous and mobile computing with a range of applications in security and biometrics, healthcare, e-learning, computer games, digital film and animation.

- Social and Affective Computing
- Assistive Robotics and Human-Robot Interaction
- Brain-Computer Interfaces
- Mobile, Ubiquitous and Pervasive Computing
- Sensor Networks and Data Analytics
- Biometric and Forensic Technologies
- Behaviour Models for Security
- Distributed Systems Security (Cloud Computing, Internet of Things)
- Advanced Pattern Recognition (medical imaging, document and handwriting recognition, animal biometrics)
- Computer Animation, Game Design and Game Technologies
- Virtual and Augmented Reality
- Digital Arts, Virtual Narratives.

- Instrumentation, Control and Embedded Systems:

The Instrumentation, Control and Embedded Systems Research Group comprises a mixture of highly experienced, young and vibrant academics working in three complementary research themes – embedded systems, instrumentation and control. The Group has established a major reputation in recent years for solving challenging scientific and technical problems across a range of industrial sectors, and has strong links with many European countries through EU-funded research programmes. The Group also has a history of industrial collaboration in the UK through Knowledge Transfer Partnerships.

The Group’s main expertise lies primarily in image processing, signal processing, embedded systems, optical sensors, neural networks, and systems on chip and advanced control. It is currently working in the following areas:

- monitoring and characterisation of combustion flames
- flow measurement of particulate solids
- medical instrumentation
- control of autonomous vehicles
- control of time-delay systems
- high-speed architectures for real-time image processing
- novel signal processing architectures based on logarithmic arithmetic.

Careers

We have developed our programmes with a number of industrial organisations, which means that successful students are in a strong position to build a long-term career in this important discipline. You develop the skills and capabilities that employers are looking for, including problem solving, independent thought, report-writing, time management, leadership skills, team-working and good communication.

Kent has an excellent record for postgraduate employment: over 94% of our postgraduate students who graduated in 2013 found a job or further study opportunity within six months.

Building on Kent’s success as the region’s leading institution for student employability, we offer many opportunities for you to gain worthwhile experience and develop the specific skills and aptitudes that employers value.

Find out how to apply here - https://www.kent.ac.uk/courses/postgraduate/apply/

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The School has a strong international reputation for research in this area and this expertise influences this course which explores current research and practice in artificial intelligence and robotics. Read more
The School has a strong international reputation for research in this area and this expertise influences this course which explores current research and practice in artificial intelligence and robotics. This MSc can lead to a career such as a designer of intelligent systems or in research. The core modules are: artificial life with robotics, neural computation and machine learning, theory and practice of artificial intelligence.

Why choose this course?

-This MSc is available with an optional one year industry placement. The 'with placement' programmes give you additional industrial experience by applying the skills you have learned throughout your studies
-One of a range of advanced courses within our postgraduate Master's programme in Computer Science, this particular course provides you with a specialism in Artificial Intelligence and Robotics
-Advanced topics studied include artificial life with robotics, neural computation and machine learning, theory and practice of artificial intelligence
-Taught by a highly-regarded and long-established computer science department
-Sixty percent of our research impact in Computer Science and Informatics at the University of Hertfordshire has been rated at world-leading or internationally excellent in the Research Excellence Framework (REF) 2014

Careers

Our master's programme is designed to give Computer Science graduates the specialist, up-to-date skills and knowledge sought after by employers, whether in business, industry, government or research.

This particular course will prepare you to take up a challenging job or to pursue further research in specific AI fields. Typical career opportunities include researcher or designer for intelligent systems.

Teaching methods

Classes consist of lectures, small group seminars, and practical work in our well-equipped laboratories. We use modern, industry-standard software wherever possible. There are specialist facilities for networking and multimedia and a project laboratory especially for master's students.

In addition to scheduled classes, you will be expected a significant amount of time in self-study, taking advantage of the extensive and up-to-date facilities. These include the Learning Resource Centres, open 24x7, with 1,500 computer workstations and wifi access, Studynet our versatile online study environment usable on and off campus, and open access to our labs.

Work Placement

All our one year full time Computer Science Masters programmes are available with an optional one year industry placement. The 'with placement' programmes give you additional industrial experience by applying the skills you have learned throughout your studies.

They offer you the opportunity to work for one year in a highly professional and stimulating environment. You will be a full time employee in a company earning a salary and will learn new skills that can't be taught at University. During the placement, you will be able to gain further insight into industrial practice that you can take forward into your individual project.

We will provide excellent academic and personal support during both your academic and placement periods together with comprehensive careers guidance from our very experienced dedicated Careers and Placements Service.

Although the responsibility for finding a placement is with you, our Careers and Placements Service maintains a wide variety of employers who offer placement opportunities and organise special training sessions to help you secure a placement, from job application to the interview. Optional one-to-one consultations are also available.

In order to qualify for the placement period you must maintain an overall average pass mark of not less than 60% across all modules studied in semester ‘A’.

Structure

Year 1
Core Modules
-Professional Issues
-Investigative Methods for Computer Science
-Artificial Life with Robotics
-Neural Networks and Machine Learning
-Theory and Practice of Artificial Intelligence
-Preparation for Placement
-Professional Work Placement for MSc Computer Science

Optional
-Professional Issues
-Investigative Methods for Computer Science
-Data Mining
-Mobile Standards, Interfaces and Applications
-Human Computer Interaction: Principles and Practice
-Advanced Databases
-Programming Paradigms
-Measures and Models for Software Engineering
-Programming for Software Engineers
-Software Engineering Practice and Experience
-Distributed Systems Security
-Secure Systems Programming
-Network System Administration
-Multicast and Multimedia Networking
-Wireless, Mobile and Ad-hoc Networking
-Information Security, Management and Compliance
-Digital Forensics
-Penetration Testing

Year 2
Core Modules
-Artificial Intelligence with Robotics Masters Project

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One of a range of degrees from the taught Master's Programme at the School of Computer Science. This course considers current research and practice in computer networking, distributed systems and security. Read more
One of a range of degrees from the taught Master's Programme at the School of Computer Science.

About the course

This course considers current research and practice in computer networking, distributed systems and security. You will develop technical expertise and practical skills in the design, management and evaluation of networks, and in the use of tools and techniques for system security.

This MSc can lead to a career such as a network system designer or administrator, or as a security consultant.

Why choose this course?

-This MSc is available with an optional one year industry placement. The 'with placement' programmes give you additional industrial experience by applying the skills you have learned throughout your studies
-One of a range of advanced courses within our postgraduate Master's programme in Computer Science, this particular course provides you with a specialism combining theoretical knowledge and practical skills in computer networking
-You will develop technical expertise and practical skills in the design,management and evaluation of networks, and in the use of tools and techniques for system security
-Taught by a highly-regarded and long-established computer science department with strong links to business
-Half the research outputs in Computer Science at the University of Hertfordshire have been rated at world-leading or internationally excellent in the Research Excellence Framework (REF) 2014

Careers

Our masters programme is designed to give Computer Science graduates the specialist, up-to-date skills and knowledge sought after by employers, whether in business, industry, government or research. This particular course will prepare you for a career such as a software engineer, developer or project manager.

Teaching methods

Classes consist of lectures, small group seminars, and practical work in our well-equipped laboratories. We use modern, industry-standard software wherever possible. There are specialist facilities for networking and multimedia and a project laboratory especially for masters students. In addition to scheduled classes, you will be expected a significant amount of time in self-study, taking advantage of the extensive and up-to-date facilities. These include the Learning Resource Centres, open 24x7, with 1,500 computer workstations and wifi access, Studynet our versatile online study environment usable on and off campus, and open access to our labs.

Work Placement

This MSc is available with an optional one year industry placement. The 'with placement' programmes give you additional industrial experience by applying the skills you have learned throughout your studies.

This offers you the opportunity to work for one year in a highly professional and stimulating environment. You will be a full time employee in a company earning a salary and will learn new skills that can't be taught at University. During the placement, you will be able to gain further insight into industrial practice that you can take forward into your individual project.

We will provide excellent academic and personal support during both your academic and placement periods together with comprehensive careers guidance from our very experienced dedicated Careers and Placements Service.

Although the responsibility for finding a placement is with you, our Careers and Placements Service maintains a wide variety of employers who offer placement opportunities and organise special training sessions to help you secure a placement, from job application to the interview. Optional one-to-one consultations are also available.

In order to qualify for the placement period you must maintain an overall average pass mark of not less than 60% across all modules studied in semester ‘A’.

Structure

Year 1
Core Modules
-Professional Issues
-Investigative Methods for Computer Science
-Distributed Systems Security
-Secure Systems Programming
-Network System Administration
-Multicast and Multimedia Networking
-Wireless, Mobile and Ad-hoc Networking
-Preparation for Placement
-Professional Work Placement for MSc Computer Science

Optional
-Professional Issues
-Investigative Methods for Computer Science
-Data Mining
-Mobile Standards, Interfaces and Applications
-Human Computer Interaction: Principles and Practice
-Advanced Databases
-Programming Paradigms
-Measures and Models for Software Engineering
-Programming for Software Engineers
-Software Engineering Practice and Experience
-Artificial Life with Robotics
-Neural Networks and Machine Learning
-Theory and Practice of Artificial Intelligence
-Information Security, Management and Compliance
-Digital Forensics
-Penetration Testing

Year 2
Core Modules
-Computer Networking Principles and Practice Masters Project

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