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
Learn how to overcome the major challenges facing industry, business and the public sector today, and influence the decision-making processes of the future.
We run a core module on Data Analytics which will introduce students to SAS Enterprise. A coursework prize for this project will be sponsored by SAS.
Recent highlights included a case study run by British Airways, a presentation from SAS on the Future of Analytics and ongoing dissertation projects with Unilever and LBM.
Assessment varies depending on course units taken. It may include a combination of course work, group project assessment and presentations, report, assignments, in-class tests and examination. The dissertation normally ranges between 12,000 and 25,000 words.
During the course you will be taking 180 credits in all. The eight taught modules during semester one and two total 120 credits and consists of both compulsory and optional taught units which can be viewed in the list below.
The core courses unit introduce you to mathematical principles and practical tools for Optimization, Decision Making, Data-Mining, Statistical Analysis, Simulation and Risk Analysis. Specific software packages include SAS, SPSS, Minitab, AMOS, Eviews, Excel, Excel Solver, SIMUL8, iThink, Risk Solver, IDS.
Over the summer period, you will carry out your Research Dissertation, worth 60 credits. Examples of recent dissertation project topics include:
Contact us for further information on scholarships available .
There are many potential career roles for postgraduates with an understanding of analytical approaches in business and management - including job titles such as operational research analyst, systems analyst, risk analyst, financial analyst, performance analyst, business analyst, marketing analyst, business modeller, and operations, logistics, production, project, risk, quality, performance, or general manager. Employers include general and specialist consultancies, the finance, retail and manufacturing sectors, government analytics units, defence and major 'solution providers' in IT systems, outsourcing and telecoms.
In many of these areas an MSc is generally accepted as highly desirable for developing an initial career in the field. In addition to preparing you for specialist professional work, the course is also a valuable preparation for further study and for research degrees.
This programme provides graduates and working professionals with a broad training in signal processing and communications. It is suitable for recent graduates who wish to develop the specialist knowledge and skills relevant to this industry and is also suitable as advanced study in preparation for research work in an academic or industrial environment or in a specialist consultancy organisation.
Engineers or other professionals wishing to participate in the MSc programme may do so on a part-time basis.
Our students gain a thorough understanding of theoretical foundations as well as advanced topics at the cutting edge of research in signal processing and communications, including compressive sensing, deep neural networks, wireless communication theory, and numerical Bayesian methods.
The MSc project provides a good opportunity for students to work on state-of-the-art research problems in signal processing and communications.
This programme is run over 12 months, with two semesters of taught courses followed by a research project leading to a masters thesis.
Semester 1 courses
Semester 2 courses
With our excellent employability record and internationally respected reputation, the University of Edinburgh is a reliable choice for developing your engineering career.
This programme will appeal to graduates who wish to pursue a career in an industry such as communications, radar, medical imaging or anywhere else signal processing is applied.