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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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The MSc in Bioengineering provides education and training to the next generation of biomedical engineers. Bioengineering is defined as the application of the principles of engineering to advancements in healthcare and medicine. Read more
The MSc in Bioengineering provides education and training to the next generation of biomedical engineers. Bioengineering is defined as the application of the principles of engineering to advancements in healthcare and medicine. Some of the most exciting work in biomedical engineering today takes place at the intersection of disciplines where the biological, physical and digital worlds intersect and have an impact on the human condition.

Students of the MSc in Bioengineering in Trinity College Dublin take lectures from experts in a variety of biomedical engineering subjects and carry out research in world class, state of the art research laboratories and facilities.

Students of the MSc in Bioengineering have the opportunity to specialise in one of three key research themes - neural engineering, tissue engineering and medical device design.

The MSc in Bioengineering with specialisation in Neural Engineering aims to provide students with the education needed to undertake neural engineering in research and clinical environments. Students receive a focused education on the key subjects of neural engineering such as Neural Signal Analysis, Implantable Neural Systems and Neuroimaging Technologies. Neural engineering has generated considerable scientific and clinical opportunities, not only for the development of interfaces between the brain and computers but also for its mostly untapped potential to help understand neurological disorders such as Parkinson's Disease or psychiatric disorders such as schizophrenia.

The MSc in Bioengineering with specialisation in Medical Device Design is designed to bring together clinicians, researchers and the medical device industry to produce new solutions for clinical needs. The field of medical device research is a fast moving area which can offer students a rewarding career in the global medical device market. Students will gain a specific education of the key topics in medical device design process and a knowledge of medical device regulation.

The MSc in Bioengineering with specialisation in Tissue Engineering provides students with an understanding of stem cells, animal/human cell culture processes, and strategies to regenerate or repair damaged tissues. This exiting multidisciplinary field of research holds significant potential in the treatment of many diseases and disorders.

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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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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

Read less
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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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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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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Launch yourself into the robotics research environment and develop the skills and confidence to conduct your own in-depth research project. Read more
Launch yourself into the robotics research environment and develop the skills and confidence to conduct your own in-depth research project. Gain current, advanced theoretical and practical knowledge from our world-leading experts in intelligent and interactive robotics. You’ll graduate ready for a future in the fast-moving world of personal and service robotics and with the skills to further your research to PhD level.

Key features

-Immerse yourself in an individual research project and learn how to communicate your motivation, methodology, and conclusions through a formal dissertation and summary paper.
-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).
-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.
-The taught elements of this programme are also delivered to students on Year 1 of the MSc Robotics Technology programme.

Course details

On this programme you’ll gain a solid and broad understanding of the latest developments and issues in robotics. You’ll build advanced 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 learn how to search, critically appraise and identify relevant research literature. You’ll also gain expertise in project management and personal effectiveness whilst immersing yourself in a substantial and 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
-PROJ510 MRes Project

Optional modules
-ROCO503 Sensors and Actuators
-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

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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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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The MRes in Neuroscience is designed to provide advanced training in neuroscience research. Students conduct a year-long research project and learn relevant techniques and skills through course work. Read more
The MRes in Neuroscience is designed to provide advanced training in neuroscience research. Students conduct a year-long research project and learn relevant techniques and skills through course work. The overall aim is to give students the necessary skill set to succeed as independent research scientists.

Course information

The MRes in Neuroscience is a full-time taught postgraduate programme run by the School of Psychology and Neuroscience.

Highlights

- Intensive week-long introductory module prepares students for the course before the start of Semester 1.
- The course includes a streamlined taught component.
- Students have the opportunity to conduct a year-long project in a single laboratory.

Teaching format

The course begins with a week-long intensive module which continues during Semester 1 with a weekly seminar series. Over two semesters, students will also complete two additional Honours-level modules.

Teaching methods include lectures, seminars, practicals and guided independent study. The modules are assessed principally by written work and oral presentations.

During Semester 1 and 2, and during the summer months, students will conduct an original research project culminating in a written thesis, which forms the main component of assessed work.

Further particulars regarding curriculum development - http://www.st-andrews.ac.uk/study/pg/taught-programmes/neuroscience/#d.en.556406

Modules

The modules in this programme have varying methods of delivery and assessment. For more details of each module, including weekly contact hours, teaching methods and assessment, please see the latest module catalogue (https://portal.st-andrews.ac.uk/catalogue/) which is for the 2016–2017 academic year; some elements may be subject to change for 2017 entry.

Compulsory modules

- Research Design in Neuroscience: intensive week-long module provides an introduction to designing and carrying out neuroscience research at the postgraduate level.
- Techniques and Skills in Neuroscience Research: examines state-of-the-art neuroscience techniques through critical analysis of primary literature.

Optional modules

Students choose two optional modules (optional modules may vary from year to year; see the University’s position on curriculum development (http://www.st-andrews.ac.uk/study/pg/taught-programmes/neuroscience/#d.en.556406)). Examples of optional modules include:

- Neurodegeneration and Aging: develops a detailed understanding of molecular neuroscience at the biochemical and molecular level.
- Motoneurons: From Physiology to Pathology: provides an in-depth knowledge of key aspects of neuronal function and potential dysfunction by focusing on motoneurons.
- Behavioural Neuroscience: allows students to access current research in the area of behavioural neuroscience. Possible topics include motivation, learning and attention.
- Vision: from Neurons to Awareness: develops an advanced understanding of the psychological processes involved in visual perception.
- Neural Basis of Episodic Memory: examines how the brain enables us to remember information from our personal experience.
- Neuromodulation: explores the diverse range of neuromodulatory mechanisms and outlines their importance in information processing in the nervous system.
- Synaptic Transmission: covers recent progress in understanding the morphology and ultrastructure of synapses, neurotransmitter corelease and recycling mechanisms, retrograde signalling, synaptic plasticity, the role of glial cells and the development of neurotransmission.
- Mechanisms of Behaviour: Integrating Psychological and Neuroscience Perspectives: explores some of the many physiological and neural systems that modulate patterns of behaviour in a range of species, including humans.

Students on this course will have the opportunity to take new modules in the academic year 2017-2018. The modules listed here are indicative, and there is no guarantee they will run for 2017 entry. There is no guarantee that these modules will run for 2017 entry. Take a look at the most up-to-date modules in the module catalogue.

Research project and thesis

Students will spend one year conducting an original research project culminating in a data-based thesis of not more than 15,000 words. The thesis will describe the research results obtained from the year-long research project and must be submitted by a date specified in August.

If students choose not to complete the thesis requirement for the MRes, there is an exit award available that allows suitably qualified candidates to receive a Postgraduate Certificate. By choosing an exit award, you will finish your degree at the end of the second semester of study and receive a PG Cert instead of an MRes.

After the MRes

Research degrees:

Many of our graduates continue their education by enrolling in PhD programmes at St Andrews or elsewhere.

The School of Psychology and Neuroscience offers a Doctor of Philosophy degree. The PhD comprises three years of full-time study and the submission of an 80,000-word thesis.

The Medical Research Council (http://www.st-andrews.ac.uk/study/pg/fees-and-funding/scholarships/research-council/mrc/) and the Biotechnology and Biological Sciences Research Council (http://www.st-andrews.ac.uk/study/pg/fees-and-funding/scholarships/research-council/bbsrc/) offers studentships for PhD research in health, biological and related sciences covering up to four years of funding and, in some cases, accommodation fees.

Careers:

A large number of Psychology and Neuroscience postgraduates have gained postdoctoral and lecturing positions in universities across the world. The School provides opportunities for students to gain academic experience by being involved in tutorials, laboratory classes and through conducting independent research.

In addition to pursuing careers in academia, postgraduates within the School have gone on to pursue careers in a variety of fields including industry, education and medicine.

The Careers Centre (http://www.st-andrews.ac.uk/careers/) offers one-to-one advice to all students on a taught postgraduate course and provides resources specific for neuroscience students (https://www.st-andrews.ac.uk/careers/students/careerdecisions/usingmydegree/neuroscience/).

Contact

School of Psychology and Neuroscience
St Mary's Quad
South Street
St Andrews
KY16 9JP

Phone: +44 (0)1334 46 2157
Email:

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