Dr. Pei Wang

We are interested in developing statistical and computational methods to address scientific questions based on data from high throughput biology/genetics experiments.  The ultimate goal is to enhance our understanding of cell activities and disease initiation/progression to a system level by integrating information from diverse biological sources (genetics/genomics, proteomics, and phenotypes). Towards this goal, efforts have been made to properly model each individual type of data and to effciently characterize interactions among different biology molecules. These efforts all borrow strength from and contribute to the developments of high dimensional inference.
Hess CSM Building 
Floor 8, S8-102                        1470 Madison Avenue          New York, NY 10029

 pei.wang at mssm.edu
 Tel:  212-824-8956
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Two Postdoc Positions Available!
Ph.D. in statistics/biostatistics or related area is required. Relevant areas of expertise include high dimensional data analysis, statistical learning, machine learning and et al. Some experience with applied techniques and analysis of data is expected. Experience with computational programming such as R and C is required.

The successful applicant will collaborate with quantitative researchers on the development of statistical and mathematical methods for analyzing and interpreting data from genomic and proteomics technologies.