PhD Studentships at Gatsby Computational Neuroscience Unit

Gatsby Computational Neuroscience Unit, UCL
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 (University College London), including Anatomy,
Computer Science, Functional Imaging, Physics, Physiology, Psychology,
Neurology, Ophthalmology and Statistics, the cross-faculty Centre for
Computational Statistics and Machine Learning. We also have links with
other UK and overseas universities including Cambridge in the UK,
Columbia, New York and the Max Planck Institute in Germany.

The Unit always has openings for exceptional PhD candidates.
Applicants should have a strong analytical background, a keen interest
in machine learning and/or neuroscience 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 machine learning
and theoretical neuroscience.

Competitive fully-funded studentships are available each year (to
students of any nationality) and the Unit also welcomes students with
pre-secured funding or with other scholarship/studentship applications
in progress.

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

Applications for 2010 entry (commencing late September 2010) should be
received no later than 6th January 2010. Shortlisted applicants will
be invited to attend interview in the week commencing 8th March 2010.