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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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Research profile. Read more

Research profile

The scientific goal of the Centre of Cognitive and Neural Systems (CCNS) is to understand information processing by the central and peripheral nervous systems, at several different levels of analysis, from cognitive psychology through cognitive neuroscience and brain imaging, behavioural neuroscience and neuropharmacology, and extending to theoretical models of neuronal networks.

Members of the CCNS are divided into different research groups with a focus on:

  • human cognitive neuroscience (including ageing)
  • the neurobiology of learning, memory and plasticity (focusing on hippocampus and cortex)
  • the processing of nociceptive somatosensory information, cerebrovascular physiology and pharmacology
  • the consequences of drug action, including drugs of abuse

Although the CCNS is hosted by the School of Biomedical Sciences, its membership is drawn from several different Schools across all three Colleges.

Training and support

During their studies, postgraduate students are assigned a personal thesis committee, which monitors progress.

Students attend seminars and the generic skills training programme provided by the Life Sciences Graduate Programme.

Postgraduates can often act as demonstrators for undergraduate teaching.

Students are strongly encouraged to present their findings at national and international conferences and to publish their findings in international journals during their postgraduate training.

Facilities

The CCNS is based at the Central Campus, and has excellent facilities for cognitive and systems neuroscience, including human cognitive neuroscience and functional MRI facilities, rodent surgical facilities, testing rooms for water mazes, event arenas, single unit recording in freely moving rodents, in vivo and in vitro (slice) electrophysiological recording, histology, confocal microscopy and wet-lab facilities.

We also offer expertise and facilities for functional imaging in animals and excellent genetic models of CNS diseases. Molecular and cellular analysis of cell death and plasticity underpin in vivo investigating.



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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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A flexible and interdisciplinary programme, which challenges you to use your specific knowledge to unravel the workings of the human brain. Read more
A flexible and interdisciplinary programme, which challenges you to use your specific knowledge to unravel the workings of the human brain.

Our brain contains many ingenious networks of millions of interconnected neurons. Together, they have a storage capacity and flexibility that far exceed modern supercomputers, or any artificial intelligent system. The Master’s specialisation in Neuroscience aims at unravelling the neuro-biological and neuro-computational mechanisms of this fascinating, complex system. We study the full spectrum from molecule to man, and from experiment to advanced theory and models.

The brain, as part of the human body, may at a first glance seem the exclusive domain of Biology. However, as the communication between neurons involves neurotransmitters and electrical ionic currents, understanding these mechanisms calls for knowledge of Chemistry and Physics. Moreover, studying mechanisms of coding and encoding of neural signals, requires advanced concepts from Mathematics and Informatics. By working together, our students learn to view complex issues from all these different sides.

Choose your own angle

Neuroscience at the Science Faculty ranges from biology to physics and mathematics, and will thus appeal to students from different Master’s programmes. The programme can be readily adapted to your individual academic background – whether that is in the field of Biology, Mathematics, Physics or Computing Science. Apart from fundamental knowledge of the brain, the Neuroscience specialisation also provides you with a general background in the principles of complex systems, and of intelligent behaviour of living and artificial systems.

Why study Neuroscience at Radboud University?

- Radboud University is the only university in the Netherlands that covers the complete research field of Neuroscience, from cognition to behaviour, and from sub-cellular processes, to single cell analysis and big data.
- The specialisation is closely connected to the world-renowned Donders Institute for Brain, Cognition and Behaviour (DI). You will get the chance to work with DI researchers during your internship, and build up a high profile network for your future career.
- The courses have a strong focus on research: they will cover the latest developments in brain research and technology, and train you the essential academic skills.
- You will work with students and researchers from different backgrounds in the natural sciences and become acquainted with a wide variety of research methods and scientific approaches.

Change perspective

The brain, as part of the human body, may at a first glance seem the exclusive domain of Biology. However, as the communication between neurons involves neurotransmitters and electrical ionic currents, understanding these mechanisms calls for knowledge of Chemistry and Physics. Moreover, studying mechanisms of coding and encoding of neural signals, requires advanced concepts from Mathematics and Informatics. By working together, our students learn to view complex issues from all these different sides.

Career prospects

Master’s specialisation in Neuroscience
The Master’s specialisation in Neuroscience gives you the chance to work at the Donders Institute for Brain, Cognition and Behaviour, and build up your own network of international renowned scientists who are working on the human brain: an excellent preparation for a future career in science. Neuroscience will also provide you with general skills that are required for any other job you aspire:
- the ability to structure complex problems
- excellent social skills for working in a multidisciplinary team
- extensive experience in presentations
- academic writing skills

Our approach to this field

At Radboud University, all branches of Neuroscience are accounted for, and strongly intertwined through the Donders Institute for Brain, Cognition and Behaviour (DI). This unique combination of expertises is a real advantage for Neuroscience students: it gives you absolute freedom to develop your knowledge in your field of interest and a high profile network for your future career.

- Science faculty
In this specialisation at the Science faculty, you will use your background in the natural sciences to unravel neurobiological processes. When completed, you will receive a Master’s degree in Medical Biology, Molecular Life Sciences, Physics & Astronomy or Science. For highly talented students it is possible to obtain a second Master’s degree at the selective Research Master’s in Cognitive Neuroscience of the DI, which has a more cognitive approach. This extra Master’s degree takes one additional year (60 EC) to complete.

- Themes
The Master’s specialisation in Neuroscience focuses on three of the four research themes of the Donders Institute for Brain, Cognition and Behaviour:

- Perception, Action and Control
Focus: Studying sensorimotor mechanisms, their cognitive and social components, their clinical implications, and their relevance for robotics.

Research: Researchers use theoretical analysis, psychophysical and behavioural studies, neurophysiological techniques, neuroimaging, clinical and pharmacological interventions, developmental and genetic approaches.

- Plasticity and Memory
Focus: The development and decay of the healthy and the maladaptive brain.

Research: Researchers in this field study the mechanistic underpinnings and behavioural consequences of long-term changes in neural structure and function. Genetic, molecular and cellular methods, animal models, as well as human neuroimaging and cognitive neuropsychology are used.

- Brain Networks and Neuronal Communication
Focus: Complex neural networks, ranging from the very smallest – communication between individual neurons – to the largest: communication between different brain areas and the outside world.

Research: The research groups combine the development of new techniques for measurements of connectivity and activation, with the experimental application of these techniques in studies of cognition in humans, non-human primates and rodents. Computational modelling is an important component.

- Custom approach
The specialisation programme depends on the Master’s programme that you will follow. In this way, it will perfectly fit to your current knowledge and practical skills. However, as all neuroscience research topics are interdisciplinary, you will become acquainted with other disciplines as well. This will help you to develop a common ground that is necessary to communicate in a multi-faceted (research) team.

See the website http://www.ru.nl/masters/medicalbiology/neuro

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Programme description. Cognitive Science is a discipline in growing demand, and Edinburgh is a widely recognised leader in this area, with particular strengths in natural language, speech technology, robotics and learning, neural computation and philosophy of the mind. Read more

Programme description

Cognitive Science is a discipline in growing demand, and Edinburgh is a widely recognised leader in this area, with particular strengths in natural language, speech technology, robotics and learning, neural computation and philosophy of the mind.

You will gain a thorough grounding in neural computation, formal logic, computational and theoretical linguistics, cognitive psychology and natural language processing, and through a vast range of optional courses you will develop your own interests in this fascinating field.

Programme structure

You follow two taught semesters of lectures, tutorials, project work and written assignments, after which you will learn research methods before individual supervision for your project and dissertation.

You will choose a ‘specialist area’ within the programme, which will determine the choice of your optional courses. The specialist areas are:

  • Cognitive Science
  • Natural Language Processing
  • Neural Computation and Neuroinformatics

Compulsory courses:

  • Informatics Research Review
  • Informatics Research Proposal
  • Introduction to Java Programming (for students who do not already meet the programming requirements for the taught masters)
  • Dissertation

There are several optional courses to choose from, such as:

  • Accelerated Natural Language Processing
  • Automated Reasoning
  • Computational Cognitive Neuroscience
  • Human-Computer Interaction
  • Machine Learning and Pattern Recognition
  • Natural Language Understanding
  • Neural Computation
  • Text Technologies for Data Science
  • Bioinformatics
  • Topics in Cognitive Modelling

Career opportunities

This programme will give you a deep understanding of the expanding domain of cognitive science through formal study and experiments. It is perfect preparation for a rewarding academic or professional career. The quality and reputation of the University, the School of Informatics and this programme will enhance your standing with many types of employer.



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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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This course provides specialist expertise in core neuroinformatics (such as computing and biology) focusing on the development of research skills. Read more
This course provides specialist expertise in core neuroinformatics (such as computing and biology) focusing on the development of research skills. It equips you with the skills to contribute to biologically realistic simulations of neural activity and developments. These are rapidly becoming the key focus of neuroinformatics research.

Newcastle is among the pioneers of neuroinformatics in the UK and hosted the £4m EPSRC-funded CARMEN project for managing and processing electrophysiology data. We are currently involved in a £10m EPSRC/Wellcome Trust-funded project. This is on implantable devices for epilepsy patients. We use computer simulations to inform about the stimulation location and protocol.

As the amount of data in the neurosciences increases, new tools for data storage and management are needed. These tools include cloud computing and workflows, as well as better descriptions of neuroscience data. Available data can inform computer simulations of neural dynamics and development. Parallel computing and new algorithms are needed in order to run large-scale simulations. There is high demand within academia as well as within industry involving healthcare informatics, brain-inspired computing, and brain-inspired hardware architectures.

The course is designed for students who have a good degree in the biological sciences (including medicine) or the physical sciences (computer science, mathematics, physics, engineering).

You will gain foundational skills in bioinformatics together with specialist skills such as computing programming, mathematics and molecular biology with a significant focus on the development of research skills.

We provide a unique, multidisciplinary experience that is essential for understanding neuroinformatics. The course draws together the highly-rated teaching and research expertise of our Schools of Computing Science, Mathematics and Statistics, Biology, Cell and Molecular Biosciences and The Institute of Neuroscience. We also have strong links with the International Neuroinformatics Coordinating Facility (INCF).

Research is a large component of this course. The emphasis is on delivering the research training you will need in the future to effectively meet the demands of industry and academia. Newcastle's research in life sciences, computing and mathematics is internationally recognised.

The teaching staff are successful researchers in their field and publish regularly in highly-ranked systems neuroinformatics journals. Find out more about the neuroinformatics community at Newcastle University.

Graduates of this course may want to apply for PhD studies at the School of Computing Science. In the past, all graduates have continued their career as PhD students either at Newcastle University or elsewhere.

Our experienced and friendly staff are on hand to help you. You gain the experience of working in a team in an environment with the help, support and friendship of fellow students.

Project work

Your five month research project gives you real research experience in neuroinformatics. You will have the opportunity to work closely with a leading research team in the School and there are opportunities to work on industry lead projects. You will have one-to-one supervision from an experienced member of the faculty, supported with supervision from associated senior researchers and industry partners as required.

The project can be carried out:
-With a research group at Newcastle University
-With an industrial sponsor
-With a research institute
-At your place of work

Delivery

The course is based in the School of Computing Science and taught jointly with the School of Mathematics and Statistics and the School of Biology, and the institutes of Cell and Molecular Biosciences, Genetic Medicine and Neuroscience.

We cater for students with a range of backgrounds, including Life Sciences, Computing Science, Mathematics and Engineering. Half of the course is taught and the remainder is dedicated to a research project. Our course structure is highly flexible. You can tailor your degree to your own skills and interests.

Semester one contains modules to build the basic grounding in, and understanding of, neuroinformatics theory and applications, together with necessary computational and numeric understanding to undertake more specialist modules next semester. Training in mathematics and statistics is also provided. Some of these modules are examined in January at the end of semester one.

Semester two begins with two modules that focus heavily on introducing subject-specific research skills. These two modules run sequentially, in a short but intensive mode that allows you time to focus on a single topic in depth. In the first semester two module, you will focus on learning about modelling of biochemical systems - essential material for understanding neural systems at a molecular level. The second module is selected from a number of options. There are up to four modules to choose from, allowing you to tailor the research training component of your degree to your preferences.

Accreditation

We have a policy of seeking British Computer Society (BCS) accreditation for all of our degrees, so you can be assured that you will graduate with a degree that meets the standards set out by the IT industry. Studying a BCS-accredited degree provides the foundation for professional membership of the BCS on graduation and is the first step to becoming a chartered IT professional.

The School of Computing Science at Newcastle University is an accredited and a recognised Partner in the Network of Teaching Excellence in Computer Science.

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Studying the cognitive and neural basis for diverse brain functions such as perception, action, language, attention and memory. Thanks to advanced brain-imaging techniques, scientists are now able to observe the human brain in action. Read more

Overview

Studying the cognitive and neural basis for diverse brain functions such as perception, action, language, attention and memory.

Thanks to advanced brain-imaging techniques, scientists are now able to observe the human brain in action. Cognitive neuroscientists therefore no longer have to rely solely on patients with brain damage to ascertain which parts of the brains are involved in which tasks and functions. They can now conduct targeted experiments on healthy persons. As a result, the discipline has gained tremendous momentum over the past twenty years.

This research Master’s programme is open to students with Bachelor’s degrees in Linguistics, Physics, Biology, Medicine, Mathematics, Behavioural Sciences, Artificial Intelligence or a related discipline. It offers an in-depth theoretical background by internationally renowned scientists in the first year. The second year is dedicated to elaborate practical training in setting up, conducting and reporting research in cognitive neuroscience. A large majority of our graduates gain a PhD position, while other graduates find jobs in the commercial sector or at research institutes.

Why study Cognitive Neuroscience at Radboud University?

- This Master’s programme is located within the world-renowned Donders Institute for Brain, Cognition and Behaviour, located on the campus of the Radboud University, with a research staff of over 500 scientists.

- Nijmegen is one of the foremost centres of cognitive neuroscience in the world. Hundreds of scientists from various faculties and top institutes have joined forces on the Radboud University campus. Besides the Donders Institute there is the Radboud university medical centre and the Max Planck Institute for Psycholinguistics. Their researchers work together very closely, exchange expertise and share state-of-the-art research equipment to unravel the workings of the human brain.

- This competitive programme provides a sound balance of theory and practice. Our selective approach guarantees excellence, especially during the research training period.

- The Radboud University campus holds a large array of state-of-the-art equipment, like labs with fMRI, MEG, EEG and eye-tracking equipment. Master’s students are free to use these, enabling you to do any type of research in this field you’d want to.

- The programme has its own, student-driven, scientific journal; based on the Stanford Exchange: Proceeding of the Master’s Programme Cognitive Neuroscience.

Specialisations

The research Master’s programme offers four specialisations that coincide with the research themes of the Donders Institute:
- Language and Communication
Studies the acquisition, understanding and production of language, and their biological underpinning.

- Perception, Action and Control
Studies basic sensorimotor aspects as well as the cognitive, contextual and social components of perception-action coupling.

- Plasticity and Memory
Studies the mechanistic underpinnings and behavioural consequences of long-term changes in neural structure and function.

- Brain Networks and Neuronal Communication
Studies the interaction between and within groups of neurons, and with the outside world

Quality label

This programme was recently rated number one in the Netherlands in the Keuzegids Masters 2015 (Guide to Master's programmes).

Our approach to this field

We have deliberately created a high admission threshold to ensure that all our students are highly motivated and have the ability to work at an advanced level. All applications are screened individually to make sure the new students meet our stringent entry criteria and help maintain the current standards of excellence.

- Multidisciplinary
Once admitted to the programme, you can expect to be trained as a multidisciplinary scientist. We offer a multi-disciplinary programme that closely involves scientists from various faculties and research institutes on campus, who come from all over the world. Their research has gained national and international recognition for its high quality. In the Master’s programme you’ll attend lectures by these top scientists. They will also supervise your practical training and the writing of a Master’s thesis in the second year.

The research you’ll become a part of addresses cross-disciplinary challenges. Besides studying the basic topics of your specialisation, you may also choose to help improve brain-computer interfaces, a hot topic with applications in medicine and information technology. Apart from being very exciting, it’s also logical that various disciplines are merging.

Our research in this field

A unique multi-disciplinary Master’s programme
Are you interested in the human brain? Would you like to conduct research into the workings of the brain and join an enthusiastic, international group of top researchers? Radboud University offers a multi-faculty Master’s programme in Cognitive Neuroscience. The programme takes two years and is of course of a scientific orientation. There is a strong emphasis on experimental research. After all, what counts is hands-on research experience. This Master’s programme is unique in Europe.

The Master’s programme in Cognitive Neuroscience is primarily focussed on training you as a researcher and if possible, a top researcher, because research institutes and businesses around the world desperately need highly qualified and motivated young researchers. Moreover, since cognitive neuroscience is a rather young discipline, much in this field has not yet been explored. There are many challenging questions that need to be answered. So there is plenty of room for new discoveries!

This competitive programme provides a sound balance of theory and practice. We enrol about 50 students per year. Our selective approach guarantees excellence, especially during the research training period.

Career prospects

This Master's programme will give you the qualifications you need to go on to get a PhD position. About 80-90% of our graduates take on a PhD project in Nijmegen or in other parts of the world. Others find jobs in the commercial sector or in research institutes.

Each year there are, on average, about 12 PhD positions available at the graduate schools Donders Graduate School for Cognitive Neuroscience (DGCN) and the International Max Planck Research School (IMPRS).

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

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Be inspired to innovate and develop the robots, artificial intelligence and autonomous systems of tomorrow’s world. Read more
Be inspired to innovate and develop the robots, artificial intelligence and autonomous systems of tomorrow’s world. Gain advanced theoretical and practical knowledge from our world-leading experts in interactive and intelligent robotics, and graduate ready to pursue an exciting career in anything from home automation to deep sea or space exploration. You’ll also have the opportunity to gain invaluable industry experience and cultivate professional contacts on an integral work placement.

Key features

-Enhance your employability and grow your professional network with an optional integral work placement. You can choose to work in the UK, or overseas in countries including France, Germany or Japan.
-Get up-to-date with the latest developments in artificial life and intelligence, adaptive behaviour, information visualisation, neural computation and dynamic systems, as well as remote access and monitoring systems. Our seminars series with speakers from industry and academia gives you the opportunity to keep ahead in this fast moving field.
-Give yourself the edge. Our programme distinguishes itself from other robotics masters programmes, in the UK and abroad, by ensuring a deeper theoretical and practical knowledge of interactive and intelligent robotics.
-Expand your skills with first-class facilities including 3D rapid prototyping systems, in-house PCB design and assembly tools, and our award winning Plymouth Humanoid robots.
-Get expert training from members of the Marine and Industrial Dynamic Analysis (MIDAS) research group and the Centre for Robotics and Neural Systems (CRNS).
-Become a professional in your field – this programme is accredited by the Institution of Engineering and Technology (IET).
-Benefit by combining disciplines that are traditionally taught separately. You’ll graduate ready with the expertise and joined-up knowledge to design and develop fully integrated mechanical, electronic, control and computing systems.

Course details

On this programme you’ll gain a solid and broad understanding of the latest developments and issues in robotics. You’ll build theoretical and practical knowledge of control and design as well as covering the interface between real-world devices, autonomous processing and evaluation of acquired information. You’ll investigate user interaction and intelligent decision-making and immerse yourself in an innovative project inspired by the latest developments in technology and society. You’ll have access to a robotics club and to a seminar series so that you can keep up-to-date with advances in the industry and academia.

Core modules
-ROCO503 Sensors and Actuators
-BPIE500 Masters Stage 1 Placement Preparation
-PROJ509 MSc Project
-AINT511 Topics in Advanced Intelligent Robotics
-MECH533 Robotics and Control
-SOFT561 Robot Software Engineering
-AINT513 Robotic Visual Perception and Autonomy
-AINT512 Science and Technology of Human-Robot Interaction

Optional modules
-BPIE502 Electrical/Robotics Masters Industrial Placement

Every postgraduate taught course has a detailed programme specification document describing the programme aims, the programme structure, the teaching and learning methods, the learning outcomes and the rules of assessment.

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The Cognitive and Decision Sciences MSc at UCL studies the cognitive processes and representations underlying human thought, knowledge and decision-making. Read more
The Cognitive and Decision Sciences MSc at UCL studies the cognitive processes and representations underlying human thought, knowledge and decision-making. It integrates a wide range of disciplines and methodologies, with the core assumption that human cognition and choice are computational processes, implemented in neural hardware.

Degree information

Key topics include the nature of computational explanation; the general principles of cognition; the scope of rational choice explanation; probabilistic models of the mind; learning and memory; and applications to economics and business. The programme involves training in experimental design and methodology, building computational models and undertaking original research.

Students undertake modules to the value of 180 credits.

The programme consists of six core modules (90 credits), two optional modules (30 credits), and a research dissertation (60 credits).

Core modules
-Introduction to Cognitive Science
-Principles of Cognition
-Research Statistics
-Research Skills and Programming for Cognitive Science
-Judgement and Decision Making
-Knowledge, Learning and Inference

Optional modules
-Applied Decision-making
-Human Learning and Memory
-Cognitive Neuroscience
-Social Cognition: Research Methods
-The Brain in Action
-Neural Computation: Models of Brain Function
-Consumer Behaviour
-Understanding Individuals and Groups
-Social Neuroscience
-Social Cognition, Affect and Motivation
-Current Issues in Attitude Research
-Talent Management
-Business Psychology Seminars
-Interpretation of Forensic Evidence
-Consulting Psychology
-Designing and Analysing fMRI Experiments

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

Teaching and learning
The programme is delivered through a combination of lectures, seminars, class presentations, and practical, statistical, computational and experimental class work. Student performance is assessed through online tests, coursework, essays, practical experimental and computational mini-projects, and the dissertation.

Careers

Students have gone on to find employment in the following areas: research, teaching, lecturing, consultancy, finance, and marketing.

For more detailed careers information please visit the department website: http://www.ucl.ac.uk/pals/study/masters/TMSPSYSCDS01

Top career destinations for this degree:
-Managing Director, Temasek International Pte Ltd
-Consumer Behaviour Research Expert, TNS
-Insight Consultant, Kantar World Panel
-Assistant Policy Adviser, Cabinet Office Behavioural Insights Team
-Software Developer, Federal Home Loan Bank of New York

Employability
On completion of the programme, students will have acquired theoretical and empirical knowledge in cognition science and decision-making, and a broad range of practical research skills. They will have made original contributions to this field in their research projects, and will understand how to apply their knowledge to real-world decision problems. They will also have developed various analytical and logical reasoning skills which can be applied to many domains of research and non-academic work. They will, in addition, have an understanding of the philosophical issues underlying cognitive science and neuroscience.

Why study this degree at UCL?

The programme draws on an outstanding faculty, ranging across many disciplines, including internationally renowned researchers in psychology, computational modelling, neuroscience and economics.

London is one of the global hot-spots for research in cognition, decision-making, and neuroscience; and it is an intellectual hub, with a high density of research seminars and scientific meetings that attract leading international researchers.

London is also one of the world's foremost commercial and political centres, with consequent opportunities for high-level applied research; and it is a vibrant, culturally diverse and international city, with world-class music, theatre and galleries.

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This postgraduate degree studies the cognitive processes and representations underlying human thought, knowledge and behaviour. It integrates a wide range of disciplines and methodologies with the core assumption that human cognition is a computational process, implemented in neural hardware. Read more
This postgraduate degree studies the cognitive processes and representations underlying human thought, knowledge and behaviour. It integrates a wide range of disciplines and methodologies with the core assumption that human cognition is a computational process, implemented in neural hardware.

Key topics include: the nature of computational explanation; general principles of cognition; methodology of computational modelling; theories of the cognitive architecture; symbol systems; connectionism; neural computation; and case studies in computational cognitive modelling.

The programme involves intensive training in experimental design and methodology, building computational models and carrying out a substantial piece of original research.

Why study this course at Birkbeck?

Draws on academics from many disciplines, including internationally renowned researchers in psychology, computational modelling and neuroscience.
Good foundation for a research career in the cognitive sciences.
Develops an understanding of core theoretical principles of human thought and an expertise in computer simulation.
Designed for graduates of either the computational sciences or the psychological sciences.
The Department of Psychological Sciences has an outstanding research tradition, with an outstanding international reputation in all aspects of cognitive neuroscience, and especially developmental cognitive neuroscience.
You will have the opportunity to interact with world-class researchers in cognitive neuroscience and cognitive neuropsychology, and attend research seminars organised by the department and a number of other local research centres and institutes.
Psychological Sciences at Birkbeck were ranked 5th in the UK in the 2014 Research Excellence Framework (REF) and we achieved 100% for a research environment conducive to research of world-leading quality.
Psychological research at Birkbeck has ranked 5th in the world in a category of the Best Global Universities Rankings 2016, an important and influential index of research quality.

Our research

Birkbeck is one of the world’s leading research-intensive institutions. Our cutting-edge scholarship informs public policy, achieves scientific advances, supports the economy, promotes culture and the arts, and makes a positive difference to society.

Birkbeck’s research excellence was confirmed in the 2014 Research Excellence Framework, which placed Birkbeck 30th in the UK for research, with 73% of our research rated world-leading or internationally excellent.

Psychological Sciences at Birkbeck were rated 5th in the UK in the 2014 Research Excellence Framework (REF) and we achieved 100% for a research environment conducive to research of world-leading quality.

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The MSc in Developmental Cognitive Neuroscience is particularly suited to students interested in the relationship between the development of the mind and the brain. Read more
The MSc in Developmental Cognitive Neuroscience is particularly suited to students interested in the relationship between the development of the mind and the brain. It combines theoretical and empirical grounding in the cognitive and biological mechanisms of developmental change with training of the analytical and practical skills required for undertaking research into cognitive development and its neural bases. The course provides perspectives from developmental cognitive neuroscience and cognitive psychology as well as hands-on training in imaging methods. Topical issues in developmental cognitive neuroscience will be covered, including the neural bases of perceiving and acting in the physical and social world and Neuroeducation.

This programme is particularly suitable for students from Psychology, Biology, Neuroscience or related disciplines who:
-Are keen to combine and integrate their interest in cognitive development and in brain development
-Wish to receive hands-on training in neuroimaging methods relevant for developmental research
-Want to conduct research into cognitive development and/or cognitive neuroscience
-Would like to get experience of working with children

Course content

The programme combines specifically focused modules relevant for Developmental Cognitive Neuroscience with courses teaching general principles of psychological research design, statistics and key transferable skills.
-Advanced Developmental Cognitive Neuroscience
-Basic Principles in Neuroimaging
-Topics in Cognitive Neuroscience
-Research Design and Analysis in Neuroimaging
-Current Questions in Developmental Research

Empirical Projects
As part of this programme, you will be given the opportunity to undertake a novel piece of empirical work, on a topic at the cutting-edge of research in developmental psychology and/or cognitive neuroscience. You will be supervised by faculty with relevant expertise in fields including language and literacy development, numerical cognition, perception, learning and memory.

Assessment
Modules are assessed through a variety of different assignments and exams including essays, critical analysis of published papers, presentations, short notes on a range of topics, practical reports, and a dissertation and poster presentation based on the Empirical Project.

Careers

This MSc course prepares students to go on to PhDs in developmental neuroscience, neuroimaging and developmental psychology. Most others opt for research and clinical assistantships to gain further experience before undertaking a PhD or training in Clinical or Educational Psychology. In both cases, the distinctive skills they gain through the MSc are highly sought after.

Other career options include business, industry, academia and administration.

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Data science is an emerging new area of science. With City’s MSc in Data Science you can develop the skills and knowledge to analyse data in many forms and communicate insights. Read more
Data science is an emerging new area of science. With City’s MSc in Data Science you can develop the skills and knowledge to analyse data in many forms and communicate insights.

Who is it for?

This programme is for students who have a numerate first degree or can demonstrate numerate skills. Students are often at the early stages of their careers in diverse professions including economics, statistics and computer science.

Students will have a curiosity about data, and will want to learn new techniques to boost their career and be part of exciting current industry developments. The MSc in Data Science includes some complex programming tasks because of the applied nature of the course, so many students have a mathematics or statistics background and enjoy working with algorithms.

Objectives

The demand for data scientists in the UK has grown more than ten-fold in the past five years *. The amount of data in the world is growing exponentially. From analysing tyre performance to detecting problem gamblers, wherever data exists, there are opportunities to apply it.

City’s MSc Data Science programme covers the intersection of computer science and statistics, machine learning and practical applications. We explore areas such as visualisation because we believe that data science is about generating insight into data as well as its communication in practice.

The programme focuses on machine learning as the most exciting technology for data and we have learned from our own graduates that this is of high value when it comes to employment within the field. At City, we have excellent expertise in machine learning and the facilities students need to learn the technical aspects of data analysis. We also have a world-leading centre for data visualisation, where students get exposed to the latest developments on presenting and communicating their results – a highly sought after skill.

Placements

There is the opportunity to do an internship as part of the programme. The final project, which is normally three months for a full-time student, can be extended to six months if you want to study within a specific organisation. When it comes to the big data and data science area, we have established relationships with organisations including the BBC, Microsoft and The British Library so you can be confident that with City, your access to professional experience is unparalleled. One recent student undertook an internship with Google and has since secured a job within the company.

Academic facilities

The School's computer science laboratories are equipped with the latest up-to-date hardware and software. From Oracle’s leading commercial object-relational database server to PCs with state-of-the-art NVidia GPUs for computer graphics, you will have access to an array of tools to support your learning.

The MSc Data Science programme offers two (three by mid 2016) dedicated computer servers for the Big Data module, which you can also use for your final project to analyse large data sets. We give you the opportunity to undertake training in MATLAB, the most popular numerical and technical programming environment, while you study.

Scholarships

A scholarship for the full fees of the MSc will be offered to an outstanding applicant. The scholarship is available to UK/EU and overseas students, studying full-time. To be considered for the scholarship, please include with your full application a one-page essay with your answer to the question:

'What are the challenges that Data Science faces and how would you address those challenges?'

The submission deadline for anyone wishing to be considered for the scholarship is: 1 MAY 2017

Teaching and learning

The teaching and learning methods we use mean that students’ specialist knowledge and autonomy increase as they progress through each module. Active researchers guide your progress in the areas of machine learning, data visualization, and high-performance computing, which culminates with an individual project. This is an original piece of research conducted with academic supervision, but largely independently and, where appropriate, in collaboration with industrial partners.

Taught modules are delivered through a series of 20 hours of lectures and 10 hours of tutorials/laboratory sessions. Lectures are normally used to:
-Present and exemplify the concepts underpinning a particular subject.
-Highlight the most significant aspects of the syllabus.
-Indicate additional topics and resources for private study.

Tutorials help you develop the skills to apply the concepts we have covered in the lectures. We normally achieve this through practical problem solving contexts.

Laboratory sessions give you the opportunity to apply concepts and techniques using state-of-the-art software, environments and development tools.

In addition to lectures, laboratory sessions and tutorial support, you also have access to a personal tutor. This is an academic member of staff from whom you can gain learning support throughout your degree. In addition, City’s online learning environment Moodle contains resources for each of the modules from lecture notes and lab materials, to coursework feedback, model answers, and an interactive discussion forum.

We expect you to study independently and complete coursework for each module. This should amount to approximately 120 hours per module if you are studying full time. Each module is assessed through a combination of written examination and coursework, where you will need to answer theoretical and practical questions to demonstrate that you can analyse and apply data science methods and techniques.

The individual project is a substantial task. It is your opportunity to develop a research-related topic under the supervision of an academic member of staff. This is the moment when you can apply what you have learnt to solve a real-world problem using large datasets from industry, academia or government and use your knowledge of collecting and processing real data, designing and implementing big data methods and applying and evaluating data analysis, visualisation and prediction techniques. At the end of the project you submit a substantial MSc project report, which becomes the mode of assessment for this part of the programme.

Course content

Data science is the area of study concerned with the extraction of insight from large collections of data.

The course covers the study, integration and application of advanced methods and techniques from:
-Data analysis and machine learning
-Data visualisation and visual analytics
-High-performance, parallel and distributed computing
-Knowledge representation and reasoning
-Neural computation
-Signal processing
-Data management and information retrieval.

It gives you the opportunity to specialise so, once you graduate, you can apply data science to any sector from health to retail. By engaging with researchers and industrial partners during the programme, you can develop your knowledge and skills within a real-world context in each of the above areas.

Core modules
-Principles of data science (15 credits)
-Machine learning (15 credits)
-Big Data (15 credits)
-Neural computing (15 credits)
-Visual analytics (15 credits)
-Research methods and professional issues (15 credits)

Elective modules
-Advanced programming: concurrency (15 credits)
-Readings in computer science (15 credits)
-Advanced databases (15 credits)
-Information retrieval (15 credits)
-Data visualisation (15 credits)
-Digital signal processing and audio programming (15 credits)
-Cloud computing (15 credits)
-Computer vision (15 credits)
-Software agents (15 credits)

Individual project - (60 credits)

Career prospects

From health to retail, and from the IT industry to government, the Data Science MSc will prepare you for a successful career as a data scientist. You will graduate with specialist skills in data acquisition, information extraction, aggregation and representation, data analysis, knowledge extraction and explanation, which are in high demand.

City's unique internships, our emphasis on machine learning and visual analytics, together with our links with the industry and Tech City, should help you gain employment as a specialist in data analysis and visualization. Graduates starting a new business can benefit from City's London City Incubator and City's links with Tech City, providing support for start-up businesses.

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The MRes is a Masters degree by research. This means that you are taught core principles and then develop these skills by doing interesting, innovative research, supported by academic staff and peers. Read more
The MRes is a Masters degree by research. This means that you are taught core principles and then develop these skills by doing interesting, innovative research, supported by academic staff and peers. This is structured so that you learn how to plan, organise and manage your time; you learn what it is to be a scientific researcher; you help contribute to the development of new knowledge; you learn intellectual skills such as argumentation, exposition, and reasoning; and you develop as an individual by improving your communication skills, writing, collaborative working and creativity.

The programme is designed for highly competent students who are keen on research-oriented Masters programmes. It consists of a mini-project in the first semester and a major research project, which will be two-thirds of the entire Masters programme. You will also study essential Research Skills, and a further 20 credits of optional modules from the following list:

Introduction to Evolutionary Computation
Introduction to Neural Computation
Intelligent Robotics (Extended)
Intelligent Data Analysis (Extended)
Planning (Extended)

Breakdown of course

Natural computation is the study of computational systems that use ideas and gain inspiration from natural systems, including biological, ecological and physical systems. It is an emerging interdisciplinary area in which appropriate techniques and methods are studied for dealing with large, complex, and dynamic problems. The aims of this programme are to:

Meet the increasing need from industry for graduates equipped with knowledge of natural computation techniques.
Provide a solid foundation in natural computation for graduates to pursue a research and development career in industry or to pursue further studies (e.g. PhD).
Give up-to-date coverage of current topics in natural computation (such as evolutionary algorithms, co-evolution, evolutionary design, nature-inspired optimisation techniques, evolutionary games, novel learning algorithms, artificial neural networks, theory of natural computation).

About the School of Computer Science

The School of Computer Science at University of Birmingham has consistently been ranked in the Top 10 in UK league tables and has regularly achieved high satisfaction scores in National Student Surveys. 95% of our students go into graduate employment (Destination of Leavers from Higher Education Survey 2014/15), and our School is ranked 8th nationally for research quality in the '2014 Research Excellence Framework'.
Our work is regularly presented in international conferences and journals, indicating the high standards we achieve in research. In 2008, the UK Funding Councils undertook a national assessment of the quality of research at British universities, the RAE. Among 81 submissions nationally for computer science, the School is equal 7th in the proportion of 4* awards, for research quality that is world-leading in terms of originality, significance and rigour.

Funding and Scholarships

There are many ways to finance your postgraduate study at the University of Birmingham. To see what funding and scholarships are available, please visit: http://www.birmingham.ac.uk/postgraduate/funding

Open Days

Explore postgraduate study at Birmingham at our on-campus open days.
Register to attend at: http://www.birmingham.ac.uk/postgraduate/visit

Virtual Open Days

If you can’t make it to one of our on-campus open days, our virtual open days run regularly throughout the year. For more information, please visit: http://www.pg.bham.ac.uk

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