NeuroAI

Machine learning and the brain solve many of the same problems. Both must extract structure from noisy, high-dimensional data, compress it, and act on it. The two fields have grown up together, and the influence runs both ways. Artificial systems give us a way to model neural computation and the circuits that support it, refining our understanding of the brain, and they provide practical tools to detect, segment and track the neural and behavioural states that experiments depend on. Equally many of the ideas at the heart of modern AI — artificial neural networks, convolutional architectures, reinforcement learning — trace their origins to neuroscience.

NeuroAI at UCL Biosciences brings together groups from across the Division working at this interface — from the biophysics of single neurons to the representations that underpin memory and behaviour. The community offers a shared home for this work: a basis for collaboration, joint grant applications, and the training of researchers fluent in both disciplines.

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We are currently recruiting two joint Lecturer/Associate Professor posts in NeuroAI across the Departments of Cell & Developmental Biology and Neuroscience, Physiology & Pharmacology. 

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