Academic

Postdoc positions in Machine Learning/Bioinformatics: Applications of dynamic graphical models to proteomics

Keywords: graphical models, dynamic graphical models, bioinformatics, proteomics, dynamic Bayesian networks, sequence modeling, machine learning, pattern recognition

The University of Washington, Seattle, department of Electrical Engineering has available a post-doctoral position in the area of statistical machine learning and bioinformatics, and in particular in the application of dynamic graphical models (such as dynamic Bayesian networks and conditional random fields) to the problem of tandem mass spectrometry (MS/MS) with the goal of the identification of proteins from complex mixtures. Other problems in proteomics are also being pursued. We are looking for a post-doctoral researcher to join a research group working on machine learning and probabilistic modeling for a diversity of scientific areas including speech and language processing, biological sequence modeling, dynamic graphical models (including DBNs, HMMs, and CRFs), polyhedral combinatorics, active and semi-supervised learning, and a variety of other applications and areas.

The position will be within the research group of Prof. Jeff Bilmes

but will also have close collaboration and regular interaction with Prof. Bill Noble and his group.

The postdoc position is for one year, but with the option for renewal for an additional year. Salary range is commensurate with other such positions and salary range is available upon request.

Applicants should send a letter explaining your research interests and experience, a complete curriculum vitae, and three letters of reference to Prof. Jeff A. Bilmes (see http://ssli.ee.washington.edu/~bilmes for email address). Letter writers should also send their recommendation letters directly to this address (email delivery is preferred).

Please use a descriptive subject line in all emails. Review of applications will start as soon as they are received and will continue until the position is filled. The position is available immediately. Please direct questions to the above email address. The University is an Equal Opportunity/Affirmative Action employer.