Duke University
Postdoctoral Fellowship in Bayesian Statistics

The Department of Statistical Science at Duke University is inviting 
applications for a postdoctoral fellow to work on Bayesian nonparametric
methods, with an emphasis on applications in machine learning and
biostatistics.  Some areas of particular interest include multi-task
learning, data fusion, joint modeling of high-dimensional data of disparate
types, functional data analysis and image analysis.  The ideal candidate
will hold a Ph.D in statistics and will have a very strong theoretical and
computational background.  This research will focus on advancing the theory
and methods available for nonparametric Bayes modeling, allowing for
learning of sparse local dependence structures in complex data.  Professor 
David Dunson will supervise the research, which will also involve 
collaborations with Professor Lawrence Carin in the Department of
Electrical and Computer Engineering at Duke.

Applicants should email their CV, a brief statement of their background
and interests and contact information for at least three references to:

David Dunson, Professor
Department of Statistical Science 
Duke University 
dunson@stat.duke.edu