Two Postdocs: Machine Learning / Bioinformatics - London / California

[Zoubin Ghahramani]

		  ** Two Postdoctoral Fellowships **

	      ** Machine Learning and Bioinformatics **

We are seeking two highly creative and motivated postdoctoral research
fellows to participate in the following research area:

  Development of Bayesian network models and machine learning methods
  for protein fold recognition. This project is part of a collaborative
  effort to develop a community resource to enable the emerging
  science of structural genomics. Candidates should have a Ph.D. in
  computational biology, computer science, machine learning,
  theoretical physics, applied mathematics, or a similar quantitative
  field and a strong interest in molecular biology.

The positions will be based in London (position 1) and Southern
California (position 2), and are described below. The positions form
part of a collaborative research project between KGI, UCL, UCSD and
the Burnham Institute.

Position 1
----------

  Gatsby Computational Neuroscience Unit
  University College London (UCL)

  http://www.gatsby.ucl.ac.uk/

Working with Dr Zoubin Ghahramani on advanced inference and learning
methods in Bayesian networks and other statistical machine learning
methods with applicability to protein fold recognition.

The Gatsby Unit at UCL is located in a quiet square in the heart of
London, providing an ideal setting for research in computational
neuroscience and machine learning in an exciting urban environment. 

Prospective candidates should apply with a cover letter, CV, and names
and email addresses of 2-3 referees. This should be sent by email to:
admin at gatsby.ucl.ac.uk, preferably using plain text, postscript or pdf
formats only.

Closing Date for applications: 31 July 2002. The position is available
immediately and the duration of the appointment is 2 years with
possibility of renewal.

Position 2
----------

  Keck Graduate Institute in Applied Life Sciences (KGI)

  http://www.kgi.edu/home.html

Working with Dr David Wild on the application of machine learning
methods to protein fold recognition. 

KGI is located 35 miles east of Los Angeles, at the foot of the San
Gabriel Mountains. Its campus is contiguous with those of the other
Claremont Colleges, which together with surrounding educational
institutions in Southern California provide a rich intellectual and
cultural environment.

Prospective candidates should apply with a cover letter and CV, and
ask for at least two letters of recommendation to be sent to Dr. David
Wild at: Keck Graduate Institute, 535 Watson Drive, Claremont, CA
91711.  Email: david_wild at kgi.edu.

The position is open immediately and applications will be reviewed as
they are received until the position is filled.