Connectionists: Gatsby PhD Programme

Peter Dayan dayan at gatsby.ucl.ac.uk
Fri Oct 12 09:09:32 EDT 2012


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, natural language processing, 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 Anatomy, Computer Science, Functional Imaging, Physics,
Physiology, Psychology, Neurology, Ophthalmology and Statistics, the
cross-faculty Centre for Computational Statistics and Machine Learning,
the forthcoming Sainsbury Wellcome Centre for Neural Circuits and
Behaviour, 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.

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


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