Postdoctoral Associate in Bayesian Statistics
The Department of Statistical Science at Duke University is inviting
applications for a Postdoctoral Associate 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 (or a related area) 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