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 Neural Computing addresses how models based on neural information processing can be used to develop artificial systems, such as neuromorphic hardware and deep neural networks, as well as the development of new machine learning and classification techniques to better understand human brain function and to interface brain and computer.
On the other hand it addresses various ways of modelling and understanding (the limitations of) cognitive processing in humans. These range from abstract mathematical models of learning that are derived from Bayesian statistics to resource-bounded computations in the brain, explainable AI, and neural information processing systems such as neural networks that simulate particular cognitive functions in a biologically inspired manner.
See the website http://www.ru.nl/english/education/masters/neural-computing/
Why study Neural Computing 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.
- 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.
- 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.
-Computational framework for counterfactual predictive processing
In a recent paper we introduced a computational framework, based on causal Bayesian networks, to computationally flesh out the predictive processing processing framework in neuroscience. In this project we want to extend this to so-called counterfactually rich generative models in predictive processing. Such models encode sensorimotor contingencies, that is, they represent 'what-if' relations between actions and sensory inputs. We aim to further operationalize this account using Pearl's intervention and counterfactual semantics. In this project you will combine formal computational modelling with conceptual analysis.
- 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 and technical expertise . 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 or joined recent startups.
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
Instead of an extended research project (45 ec) you can also choose to do a smaller (30 ec) research project plus a 15 ec internship, giving you plenty of hands-on experience with AI. We encourage students to do this internship abroad.
*Subject to validation
The Msc Games Development course provides students with a higher-level understanding and direct professional experience through a multidisciplinary approach across commercial game projects.
This course is ideal for graduates who have completed our BA (Hons) Computer Games Design or BSc (Hons) Computer Games Programming undergraduates degree, as well as those who have graduated from other related technical and creative subject areas who are wanting to enter the video games industry.
We have collaborative partnerships in place with community organisations and employers including commercial and third sector organisations.
Students will be exposed to work on commercial games, providing them with an understanding of business and enterprise as well as preparing students for working within a commercial studio setting.
One of our modules allows students to link up with the Ipswich Waterfront Innovation Centre (IWIC), providing them with access to more facilities and covering a range of business-related topics in connection with games development.
Development Management (mandatory)
This module provides students with industry standard management methodologies and tools used to run team game developments.
Visual Scripting (mandatory)
In this module. students learn how to develop games using visual scripting tools at high and low levels, depending on their discipline and background.
Group Project 1 - Multiple Rapid Prototyping (mandatory)
For this group project, students concept and rapidly develop game ideas, learning how to work efficiently as a team.
Group Project 2 (mandatory)
In this module, students will work on a longer 12-week development project.
Business Development (mandatory)
This moduled covers a range of core business skills relevant to both the independent and large scale development studios. This will be delivered by the Ipswich Waterfront Innovation Centre (IWIC) where students will have access to the Entrepreneurial Programme as well as unlimited access to the IWIC facilities.
Final Project (mandatory)
The Final Project involves independent learning as an extended dissertation covering a detailed exploration of an element of the games industry.
Research Methods (mandatory)
In this module, students will learn rigorous academic and commercial research skills.
Work-based practice is embedded throughout the duration of the course. All modules will relate to work-based learning, relating to commercial management processes or understanding production within a working environment. This will enhance employability and give graduates a greater understanding of games development within the work place.
Graudates can progress in to a range of careers including: Game Programmer, Games Designer, Games Artist, Quality Assurance, Serious Games Developer and Gamification Developer to name a few.
The MSc Game Development course will have access to the Eclipse Suite where students can access the facilities on specific days for independent working and group projects.
Students can benefit from a dedicated lab, access to two other game development labs and a range of game development hardware including, Oculus Rift, Emotive EPOC+ Brain interface, Leap motion, Myo, Phidget components for building custom game controllers, a range of mobile phones and tablets to test your games on.
Students will also have access to a common room area for MSc students and a custom games cabinet in which to run student games.
