JOB: Research Fellow Position at University of Edinburgh

[Chris Williams]

 3 year Research Fellowship in Machine Learning and Probabilistic Modelling

The University of Edinburgh seeks a Research Fellow in the field of
Machine Learning and Probabilistic Modelling.

The successful candidate will work closely with Dr Chris Williams and
be based in the Institute for Adaptive and Neural Computation (ANC) in
the School of Informatics. The fellowship offers considerable
flexibility regarding the areas of research to be pursued within the
general field of Machine Learning and Probabilistic
Modelling. Examples of possible research areas include (but are not
limited to) supervised learning, unsupervised learning, probabilistic
graphical models, and learning in computer vision.  Current areas of
research activity include supervised learning using Gaussian process
predictors, learning objects from image data, latent variable models
(e.g. applied to galaxy spectra) and advanced factorial-type Hidden
Markov models for condition monitoring in premature babies. Research
in Machine Learning/Probabilistic Modelling in ANC is led by Dr. Chris
Williams, Dr. David Barber and Prof. Chris Bishop.


The candidate should have postgraduate experience in the
mathematical, physical or computing sciences. Previous experience with
probabilistic modelling together with good software skills would be an
advantage.  The candidate should be highly motivated and keen to
participate in a lively interdisciplinary environment.

The fellowship is available for a period of three years and is
supported by a grant from MSR (Europe) to support basic research.

Application Procedure: Please see details at
http://www.informatics.ed.ac.uk/events/vacancies/311653.html
The closing date for applications is 23 August 2002.

For informal enquiries please contact Dr Chris Williams,
c.k.i.williams at ed.ac.uk, tel +44 131 651 1212.