Our Master's degree in Biomedical Engineering first began in 1991 and provides all of the necessary technical knowledge, expertise and transferable skills to succeed in one of the fastest growing engineering disciplines. This degree offers four distinct steams, each of which accredited and employment-focused:
Biomedical Engineering with Medical Physics and Imaging.
Biomedical Engineering with Biomechanics and Mechanobiology
Biomedical Engineering with Neurotechnology
Biomedical Engineering with Biomaterials and Tissue Engineering
The Medical Physics stream trains graduates in the physical understanding required for healthcare and medical research, focusing on human physiology, and the use of radiation in treatment and in clinical imaging (especially MRI, ultrasound, X-ray and optical techniques), as well as the signal and image processing methods needed for the design and optimal use of such systems in diagnosis and research.
The Biomechanics stream is focused on bioengineering problems related to major diseases associated with an ageing population, such as cardiovascular disease, glaucoma, and bone and joint disease (osteoarthritis, osteoporosis).
These are major causes of mortality and morbidity, and this stream prepares engineers for a career in these key growth areas.
The Neurotechnology stream covers the development of new technology for the investigation of brain function, focusing on the application of this to benefit society—for example the development of neuroprosthetic devices, new neuroimaging techniques, and developing drugs and robotic assistive devices for those with central nervous system disorders, as well as in biologically-inspired control engineering.
The Biomaterials stream is offered jointly with the Department of Materials.
It addresses the selection and use of biomaterialsin medical and surgical devices, including their application, properties, interaction with tissues and drawbacks. Existing and new biomaterials are studied, including bioactive and biodegradable materials, implants and dental materials.
Modules also cover the development of materials for new applications, the response of cells and the design of materials as scaffolds for tissue engineering, which involves tailoring materials so that they guide stem cells to produce new tissue.
You will be required to choose your stream at the time of application. All four streams lead to the award of the MSc in Biomedical Engineering. The Medical Physics and Biomechanics streams are accredited by the Institute of Physics and Engineering in Medicine (IPEM).
The course is full-time for one calendar year, starting in October. It currently has an annual intake of about 100 students.
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