Postdoctoral Associate in Bayesian Statistics

The Department of Statistical Science at Duke University is inviting 
applications for a Postdoctoral Associate to work on Bayesian methods for 
massive dimensional predictors, with an emphasis on applications to 
studies of gene-environment interactions and complex phenotypes. Some 
areas of particular interest include random and nonlinear projections for 
dimensionality reduction, sparse latent factor models and Bayesian
nonparametrics.  The ideal candidate will hold a Ph.D in statistics or a
related field and will have a very strong theoretical and computational 
background.  This research will focus on advancing the theory and methods 
available for massive dimensional predictors, with an emphasis on 
practically useful methods that can be applied broadly by non-statisticians.  

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