Gatsby Unit PhD Programme in Theoretical Neuroscience and Machine Learning -- deadline 13 November
Applications to the Gatsby Unit PhD programme close soon. See www.ucl.ac.uk/gatsby/study-and-work/phd-programme The Gatsby Unit is a leading research centre focused on theoretical neuroscience and machine learning. We study (un)supervised and reinforcement learning in brains and machines; inference, coding and neural dynamics; Bayesian and kernel methods, and deep learning; with applications to the analysis of perceptual processing and cognition, neural data, signal and image processing, machine vision, network data and nonparametric hypothesis testing. The unit provides a unique opportunity for a critical mass of theoreticians to interact closely with one another, with the Sainsbury Wellcome Centre for Neural Circuits and Behaviour (SWC), the Centre for Computational Statistics and Machine Learning (CSML), other research groups in related UCL departments, and the nearby Alan Turing and Francis Crick Institutes. Students complete a 4-year PhD in either machine learning or theoretical neuroscience, with minor emphasis in the complementary field. Courses in the first year provide a comprehensive introduction to both fields and systems neuroscience. Students are encouraged to work and interact closely with researchers at the SWC and/or CSML to take advantage of this uniquely multidisciplinary research environment. Applicants should have a strong analytical and quantitative background, a keen interest in neuroscience, machine learning or both, and a relevant first degree, for example in Mathematics, Statistics, Computer Science, Engineering, Physics, Neuroscience or Cognitive Psychology. Full funding is available regardless of nationality. The unit also welcomes applicants who have secured or are seeking funding from other sources. Applications should be submitted directly via our online portal. -- Maneesh Sahani, Ph.D. Professor of Theoretical Neuroscience and Machine Learning Director, Gatsby Computational Neuroscience Unit, UCL 25 Howland Street, London W1T 4JG
participants (1)
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Maneesh Sahani