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ALLSTAT  January 2012

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Subject:

Postdoctoral Positions in Machine Learning - University of Cambridge

From:

Zoubin Ghahramani <[log in to unmask]>

Reply-To:

Zoubin Ghahramani <[log in to unmask]>

Date:

Tue, 17 Jan 2012 15:21:55 -0500

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   UNIVERSITY OF CAMBRIDGE

   Postdoctoral Research Associate Positions in Machine Learning

   http://mlg.eng.cam.ac.uk
 
We are seeking up to three highly creative and motivated Postdoctoral Research Associates to join the Machine Learning Group in the Department of Engineering, University of Cambridge, UK, working with Professor Zoubin Ghahramani.  The group is one of the world’s leading centres for Bayesian statistical Machine Learning and successful candidates will be expected to have a strong publication record in this field.
 
* Postdoc 1: will do research on developing novel advanced algorithms for probabilistic modelling applicable across a range of physical, biological and social sciences. Experience in Bayesian nonparametrics is desirable. The position will be for two years, with possible extension for a further year.
 
* Postdoc 2: will work in some subset of the areas related to Gaussian processes, statistical time-series modelling, approximate inference, and Bayesian nonparametrics. This project is funded through a grant on advanced algorithms for neural signal modelling, and involves a collaboration with Washington University in St Louis. This position is for one year in the first instance.
 
* Postdoc 3: will help with research on 'Learning to Answer Natural Language Database Queries' in collaboration with the Machine Learning and Perception Group at Microsoft Research Cambridge. The ideal candidate would have a strong background in probabilistic machine learning and language modelling.
 
All positions are available now and can start as soon as the successful applicant is appointed.
 
The successful applicant will have or be near completing a PhD in computer science, engineering, probability, statistics or a related area, and will have extensive research experience and a strong publication record in statistics, probability, or machine learning. Preference will be given to applicants with some experience in large-scale modelling with Bayesian methods, non-parametric Bayesian models, and approximate inference.

Please apply, via email, to Diane Unwin, Department of Engineering, (email [log in to unmask] , Tel +44 01223 748529). Please email a completed form CHRIS /6 (cover sheet for C.V.s) available at http://www.admin.cam.ac.uk/offices/hr/forms/ with your C.V. (which should include a list of your publications and names of at least two referees) and a covering letter indicating which posts you wish to be considered for, in pdf format. Please quote Reference: NA12322.

Applications should be sent so as to reach us not later than ** 19th February 2012 ** .


--- 

Zoubin Ghahramani
Professor of Information Engineering
University of Cambridge
http://learning.eng.cam.ac.uk/zoubin/

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