Connectionists: Gatsby PhD Programme

[Peter Dayan]

Gatsby Computational Neuroscience Unit, University College London
			  4 year PhD Programme

The Gatsby Unit is a centre for theoretical neuroscience and machine
learning, focusing on unsupervised, semi-supervised and reinforcement
learning, neural dynamics, population coding, Bayesian and nonparametric
statistics, kernel methods, and applications of these to the analysis of
perceptual processing, neural data, machine vision and bioinformatics.
It provides a unique opportunity for a critical mass of theoreticians to
interact closely with each other, and with other world-class research
groups in related departments at UCL, including the Sainsbury Wellcome
Centre for Neural Circuits and Behaviour, with which we will shortly
share a building, and Biosciences, Computer Science, Functional Imaging,
Physics, Physiology, Psychology, Neurology, Ophthalmology and
Statistics, the cross-faculty Centre for Computational Statistics and
Machine Learning, and also with other UK and overseas universities.

The Unit has openings for exceptional PhD candidates. Applicants
should have a strong analytical background, a keen interest in
neuroscience and/or machine learning and a relevant first degree, for
example in Computer Science, Engineering, Mathematics, Neuroscience,
Physics, Psychology or Statistics.

The PhD programme lasts four years, including a first year of intensive
instruction in techniques and research in theoretical neuroscience and
machine learning.

All students are fully funded, regardless of nationality. The Unit
also welcomes applications from students with pre-secured funding or
who are currently soliciting other scholarship/studentships. The closing
date for applications is 16th December 2013.

Full details of our programme, and how to apply, are available at:
http://www.gatsby.ucl.ac.uk/teaching/phd

For further details of research interests please see
http://www.gatsby.ucl.ac.uk/research.html
and the individual faculty webpages at
http://www.gatsby.ucl.ac.uk/members.html