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.
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.
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.
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
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
The Institute for Integrated Micro and Nano Systems (IMNS) brings together researchers from integrated-circuit design, system-on-chip design, image-sensor design, bioelectronics, micro/nano-fabrication, microelectromechanical systems (MEMS), micromachining, neural computation and reconfigurable and adaptive computing.
Research interests include low-level analogue, low-power, adaptive and bio-inspired approaches, system-on-chip computing and applications from telecommunications to finance and astronomy. There is also a research focus on integrating CMOS microelectronic technology with sensors and microsystems/MEMS to create smart sensor systems. We also have a strong and growing interest in applications relating to life sciences and medicine, with particular focus on bioelectronics, biophotonics and bio-MEMS.
IMNS has laboratory facilities that are unique within the UK, including an advanced silicon and MEMS micro-fabrication capability coupled with substantial design and test resources. The Institute has an excellent reputation for commercialising technology.
The development of transferable skills is a vital part of postgraduate training and a vibrant, interdisciplinary training programme is offered to all research students by the University’s Institute for Academic Development (IAD). The programme concentrates on the professional development of postgraduates, providing courses directly linked to postgraduate study.
Courses run by the IAD are free and have been designed to be as flexible as possible so that you can tailor the content and timing to your own requirements.
Our researchers are strongly encouraged to present their research at conferences and in journal during the course of their PhD.
Every year, the Graduate School organises a Postgraduate Research Conference to showcase the research carried out by students across the Research Institutes
Our researchers are also encouraged and supported to attend transferable skills courses provided by organisations such as the Engineering and Physical Sciences Research Council (EPSRC).
An MSc by Research is based on a research project tailored to a candidate’s interests. It lasts one year full time or two years part time. The project can be a shorter alternative to an MPhil or PhD, or a precursor to either – including the option of an MSc project expanding into MPhil or doctorate work as it evolves. It can also be a mechanism for industry to collaborate with the School.
The Institute has laboratory facilities that are unique within the UK, including a comprehensive silicon and MEMS micro-fabrication capability coupled with substantial design and test resources.
The Institute has an excellent reputation for commercialising technology.
Control Engineering is a multi-disciplinary subject, with applications across a wide range of industrial sectors. The Control Systems Group in the School of Electrical and Electronic Engineering at the University of Manchester has been running an MSc course in Advanced Control and Systems Engineering since 1968. The course is geared for graduates from a variety of scientific and engineering disciplines.
The aims of the course are to:
Students acquire a range of intellectual skills that cover the design, analysis and simulation of control systems. A strong emphasis is placed on practical and transferable skills through laboratory exercises and the use of software packages.
The taught part of the course comprises six course units of 15 credits each. This is assessed by written examinations, coursework and laboratory reports.
A strong feature of the course is the dissertation project, which constitutes 60 Credits. The project introduces students to cutting edge control theory and applications.
Typical course units include Control and Computer Laboratory, Linear Optimal Control, Intelligent Systems, Non-linear Controllers & Systems, Self-tuning and Adaptive Systems, Manufacturing Automation and Data Engineering, Fault Detection and Diagnosis, and Process Control Systems.
Practical support and advice for current students and applicants is available from the Disability Advisory and Support Service. Email: [email protected]
In 2008 we celebrated the 40 th anniversary of our MSc course. In that time graduates of the course have achieved top ranking industrial and academic positions in their home countries, in the UK and around the world.
Graduates from the course are employed in a variety of industries, including process and petro-chemical industries, manufacturing, power generation and the automotive and aerospace sectors. Recently there has been a surge in demand for control engineers in the field of biomedicine. More generally feedback control and systems engineering skills play an important part in an ever widening range of high tech applications.
The MSc can also be used a spring board for postgraduate research. Approximately 50% of the current PhD students in the Control Systems Group are graduates from the MSc course.