Understanding the brain is one of today’s biggest scientific challenges.
It is not only important for basic science and health, but many researchers believe that a computational description of the brain is required to further advance artificial intelligence.
This doctoral training programme focuses on computational understanding and analysis of the brain, including how it processes information.
Specific projects may involve developing computer simulations, training neural networks, developing new data analysis methods or mathematical analysis.
When you start, you’ll work with your supervisor to design a study plan based on which courses are best suited to you and your project. You will learn basic concepts in the field through tutor-guided sessions, and will also take part in a weekly journal club with fellow students to discuss internal and external research developments.
Applicants should have a background in psychology, mathematics, biology, physics, computer science or a related discipline, as well as strong quantitative skills (prior biology knowledge is not required). For more information, contact the academic lead: Mark van Rossum, School of Psychology.
Example projects include:
Computational neuroeconomic (Christopher Madan) Novel measures of brain morphology (Christopher Madan) Movement of ions in neurons and other structures (Mark van Rossum and Paul Smith) Neural networks with frugal learning(Mark van Rossum) Modelling the formation of new memories in the human brain (Matias J. Ison and Stephen Coombes)
Integration of stimulus statistics and reward over time (Nikos Gekas) Modelling complex natural motion perception (Alan Johnston and Neil Roach ) Mapping the wires from neural activity (Mark Humphries) Bayesian analysis of behavioural strategies (Mark Humphries) Divergent networks (Mark Humphries and Ruediger Thul ) Age-related changes in brain connectivity and cognition studied through machine learning (Martin Schürmann, Andrew Reid, Christopher Madan ) Modeling the effects of internal and external noise on perceptual Systems(Tim Ledgeway and Paul McGraw)
Posted on Tuesday 26th March 2019