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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

Radboud University Master's Open Day 10 March 2018



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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

Radboud University Master's Open Day 10 March 2018



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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 the philosophy of the mind. Read more

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 the 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 option 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 Project 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
  • Computational Cognitive Neuroscience
  • Human-Computer Interaction
  • Machine Learning and Pattern Recognition
  • Natural Language Understanding
  • Neural Computation
  • Text Technologies for Data Science
  • Bioinformatics

Career opportunities

This programme will give you a deep understanding of the expanding domain of cognitive science through formal study and experiments. It is excellent 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. Recent graduates are now working as software engineers, analysts and language scientists for companies such as British Telecom and Intel.



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About the course. 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

First semester

• Research Methods

• Artificial Intelligence Programming

• Mobile Robots

• Fuzzy Logic

Second semester

• Artificial Neural Networks

• Computational Intelligence Optimisation (CIO)

• Applied Computational Intelligence

• Data Mining, Techniques and Applications

(Intelligence Systems only)

• Intelligent Mobile Robots (Intelligent Systems

and Robotics only)

Third semester

• Individual Project

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
About the course. 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

First semester

• Research Methods

• Artificial Intelligence Programming

• Mobile Robots

• Fuzzy Logic

Second semester

• Artificial Neural Networks

• Computational Intelligence Optimisation (CIO)

• Applied Computational Intelligence

• Data Mining, Techniques and Applications

(Intelligence Systems only)

• Intelligent Mobile Robots (Intelligent Systems

and Robotics only)

Third semester

• Individual Project

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.

You will have dedicated computing facilities in the School of Computing. You will have access to the latest tools for system analysis and development. For certain projects, special facilities for networking can be set up.

You will enjoy access to specialist IT facilities to support your studies and access to a Linux based website that you can customise with PHP hosting services.



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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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Why study at Roehampton. Develop advanced research skills required in preparation for your career within biomedical research, a clinical environment, or in the health industry. Read more

Why study at Roehampton

  • Develop advanced research skills required in preparation for your career within biomedical research, a clinical environment, or in the health industry.
  • Collaborate with leading, internationally renowned experts in the field who will teach topical and current issues in biomedicine.
  • Conduct your own research project in our state-of-the-art molecular biology laboratories equipped with microscopy analysers, autoradiography, flow cytometry, high sensitivity HPLC and LC-MS, and neural stem cell and tissue culture facilities.
  • We are the most research-intensive modern university in the UK (Research Excellence Framework 2014).
  • Roehampton is ranked best modern university in London (Sunday Times Good University Guide 2016).

Course summary

This innovative degree offers a fascinating opportunity to study modern and topical research areas in Cell Biomedicine. You will gain the essential skills required to prepare for your career in either biomedical research, a clinical setting or within the health industry.

This postgraduate degree will provide you with advanced research training in medical aspects of cell biology and pathology and you will conduct your own lab based research project. With a focus on research methods, you will take you research methods to the next level in producing your own research design, understanding ethics in research projects and best practice in handling statistical data-sets. The programme includes a variety of subject-specific lectures, seminars, tutorials and practical work that will give keep you up-to-date with the current advances in the field. You will learn the theoretical and technological aspects of cellular biomedicine and their practical applications within industry.

You will be taught by enthusiastic, research active experts in the field who conduct research in a diverse range of topics that you can choose to study such as cellular and molecular mechanisms of cancer, microbial resistance to antibiotics, immune mechanisms of disease, stem cell research and molecular modelling in cell biology.

You will conduct your research project in our state-of-the-art laboratories equipped with microscopy analysers, autoradiography, flow cytometry, high sensitivity HPLC and LC-MS, and neural stem cell and tissue culture facilities.

You will automatically be a part of our Health Sciences Research Centre, a community of leading experts who are currently investigating a range of topical issues. You will participate in engaging discussions within research seminars on the latest developments within neuroscience and the health sciences.

Content

In this postgraduate programme, you will be trained in medical aspects of cell biology and pathology with a focus on the lab based research project. The programme has a strong focus on research methods and will provide you with necessary skills in research design, ethics and statistical methods.

You will learn the most recent advances in cellular biomedicine by being part of engaging subject-specific lectures, seminars, tutorials and conducting your own research. You will study the theoretical and technological and their practical applications in cellular biomedicine.

Modules:

  • Research Project
  • Research Methods
  • Cells, Disease and Therapy
  • Communication

Career options

This postgraduate programme provides both a solid academic basis and practical hands-on experience in the area of cellular biomedical sciences. It will prepare you for careers in academia, clinical research, the health industry or within government organisations.

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High standards: . Read more

High standards: The Bordeaux International Master of Neuroscience emphasises training in cutting-edge techniques in all major topics of brain research, from molecules to cognition. Its main objective is to foster Neuroscience education and train new brain scientists, by offering a unique interdisciplinary and integrated approach from normal brain functions to brain disorders.

Excellent teaching: In Bordeaux, about 30 professors and lecturers in Neuroscience are involved in teaching as well as many neuroscientists and colleagues specialized in psychology, cognition, modeling, physiology, genetics, medicine, brain imaging, etc.

Top research/traineeships: Neuroscience in Bordeaux has grown over the last 15 years to become one of the largest Neuroscience scientific communities in France and in Europe, with over 600 people working in the various Neuroscience laboratories of the University of Bordeaux. In order to meet the most important challenges facing Neuroscience research, all these laboratories are grouped within a virtual institute, called the Bordeaux Neurocampus, a multidisciplinary consortium of world renowned scientists. Bordeaux Neurocampus offers, together with our international academic partners, excellent opportunities for traineeships.

Interaction with the professional sector: Students have access to Pharma multinationals for traineeships through internationally oriented consortia such as Pierre Fabre, Sanofi-Aventis, Glaxo-SmithKline etc.

Program structure

International mobility is highly recommended for at least one of the two traineeships. Mobility fellowships are provided upon application.

Year 1: 

Semester 1: September - January (30 ECTS)

Compulsory courses

  • Scientific Communication (3 ECTS)
  • Statistics and Neural Modelling (3 ECTS)
  • Tutored Project (3 ECTS)
  • Functional Neuroanatomy (5 ECTS)
  • Neurophysiology (4 ECTS)
  • Molecular Neurobiology, Development & Neurogenetics (4 ECTS)
  • Neuropharmacology (4 ECTS)
  • Higher Brain Functions (4 ECTS)

Semester 2: January - June (30 ECTS)

  • Laboratory Internship

Year 2: 

Semester 3: September - January (30 ECTS)

Compulsory courses

  • Research Project Literature Survey & Methodology (9 ECTS)
  • Industrial Research (3 ECTS)

Optional courses

  • Cellular and Molecular Neurobiology (6 ECTS)
  • Cognitive Neuroscience (6 ECTS)
  • Pathophysiology of Neurological & Psychiatric Diseases (6 ECTS)
  • Neural Networks (6 ECTS)
  • Addiction (6 ECTS)
  • Experimentation in Behavioural Studies (6 ECTS)
  • Pharmacology of Psychotropic Drugs (6 ECTS)

Semester 4: January - June (30 ECTS)

  • Master Thesis Project

Strengths of this Master program

  • Advanced scientific education and training with innovative and interdisciplinary brain research methodology.
  • Training through original research.
  • Small classes and close contact with faculty staff.
  • Opportunities for international mobility.

After this Master program?

After graduation, students have access to career opportunities in the industrial sector, in clinical research or may carry out further fundamental research as PhD students.



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Studying both cognitive neuroscience and neuropsychology will give a thorough grounding in the scientific investigation of the neural mechanisms underlying human behaviour and the effects of brain injury on cognitive function. Read more

Studying both cognitive neuroscience and neuropsychology will give a thorough grounding in the scientific investigation of the neural mechanisms underlying human behaviour and the effects of brain injury on cognitive function. You will be taught the theoretical and biological foundations of cognitive science, and undertake advanced training in statistics and neuropsychological research methods.

Cognitive neuroscience is the scientific study of biological substrates underlying cognition, with a focus on the neural substrates of mental processes. It is a branch of both psychology and neuroscience, overlapping with disciplines such as biological psychology, cognitive psychology and neuropsychology. Cognitive neuropsychology uses data from single cases of individuals with brain injury or neurological illness to refine theoretical models of cognitive processing.

You explore topics including:

  • The physiological bases and practical applications of cognitive neuroscience techniques
  • How brain activity translates into cognitive processes
  • The theoretical and biological foundations of cognitive science
  • How brain damages impact on cognitive functions
  • Cognitive neuroscience of language
  • Cognitive neuropsychology of reading and face processing

Our research is challenging and ground-breaking, with 90% rated ‘world-leading’ or ‘internationally excellent’ (REF 2014), placing us in the top 15 in the UK. We are supported by some of the most prestigious funding bodies, including the ESRC, European Commission and the Leverhulme Trust.

We are a warm and friendly Department, and we wish to welcome recent graduates of psychology (or a closely related subject such as cognitive science). This course is popular with international students (particularly those from North America). Our students receive a high quality Masters degree within one year and benefit from small class sizes and strong research training.



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Understanding the relationship between brain, cognition and behaviour is one of the biggest challenges the scientific community is currently working on. Read more

Understanding the relationship between brain, cognition and behaviour is one of the biggest challenges the scientific community is currently working on. Computational cognitive neuroscience is a young and exciting discipline that tackles these long-standing research questions by integrating computer modelling with experimental research.

This Masters programme will foster a new generation of scientists who will be trained in both neuro-computational modelling as well as cognitive neuroscience. Its core topics include:

  • Creating computational/mathematical models of neurons, circuits and cognitive functions
  • The fundamentals of cognitive neuroscience (brain mechanisms and structures underlying cognition and behaviour)
  • Advanced data analysis and neuroimaging techniques

The programme is suitable for students from a variety of disciplines including - but not limited to - psychology, computing, neuroscience, engineering, biology, maths and physics. Students with no prior programming experience are welcome.

Graduates of this Masters will acquire a unique set of complementary skills that will make them extremely competitive in securing research or analyst positions in both academia and industry.

Why study this course?

  • This cutting-edge programme is at the forefront of a new, rapidly emerging field of research.
  • It is multidisciplinary, conveying the theory and practice of computational and cognitive neurosciences.
  • Graduates of this programme will gain a competitive edge in the job market over graduates of other, standard programmes in related fields.

Modules & structure

You will study the following core modules:

You will also undertake a 60 credit research project investigating an aspect of cognitive neuroscience using computational modelling, advanced data analysis methods, or a combination of these techniques. Culminating in a 10,000 word dissertation, the project will be carried out by combining the computational, experimental and data analysis skills that students will acquire over Term 1 and 2.

Option modules

You will choose one option from the following two modules:

  • Data Programming
  • Introduction to MATLAB

You will also choose one of the following 4 options:

Please note that due to staff research commitments not all of these modules may be available every year.

Skills & careers

Graduates of this programme will have the following assets in their portfolio:

  • A sound understanding of brain mechanisms and structures underlying cognition and behaviour
  • Knowledge or experience of experimental cognitive neuroscience methods
  • Skills in statistical data analysis
  • Knowledge of theory and practice of biologically constrained neural models of human brain function
  • Computer programming skills.

Such a cross-disciplinary profile will make graduates of this Masters particularly competitive on the job market, especially when applying for positions that require complementary expertise and skills.

The course prepares students for employment in areas including cognitive neuroscience, IT consultancy, cognitive robotics, as well as large enterprises developing software systems inspired by human cognition (e.g., web-search engines, systems for natural language processing, information extraction, data mining and human-computer interaction).

The course is also ideal preparation for further study at PhD level.



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