Computational Neuroscience, Cognition and AI

Entry requirements

Undergraduate degree 2:1 (or international equivalent). For quantitatively minded students with a background in psychology, neuroscience, or biosciences as well as those with training in physics, engineering, mathematics, or computer science; no specific biology or psychology knowledge required.

Work experience

This course requires strong mathematical and programming skills. In their final two years of study, applicants must have achieved a 2.1 (60%) in 2 module(s) covering at least two of the following subjects: mathematics, statistics, physics, data analysis, computer science. If such skills were gained independently, evidence should be provided.

In exceptional cases a 2:2 degree (or international equivalent) may be considered provided the applicant has at least one year of relevant work experience or another supporting factor.

Months of entry

September

Course content

This unique interdisciplinary course combines aspects of psychology, mathematics and computer science. It uses computational models and artificial intelligence to further the understanding of the brain.

You will learn how:

• the brain is believed to work on the cellular, network and systems level
• to develop mathematical models of brain function and use them in simulations
• cognitive phenomena relate to brain activity
• current AI algorithms are based on neuroscience findings
• a range of experimental approaches are used to measure and analyse brain function.

There will be particular focus on how:

• memories are stored and organised in the brain
• networks of neurons perform computations
• visual illusions find their origins in neural circuits.

Our research covers many aspects of computational study on the brain, from the changes at a single synapse through to the behaviour of large populations.