Applications are invited for a postdoctoral fellow position to join Dr. Xiang Zhou’s research group in the Department of Biostatistics at the University of Michigan. This position emphasizes developing statistical methods and computational tools for high-dimensional biological data from genome-wide association studies and/or functional genomics sequencing studies. Specific areas of interest include, but are not limited to, (1) SNP heritability estimation and phenotype prediction using dense genotypes and/or sequence data; (2) integrative modeling of complex traits with genotypes, expression and other omics data; (3) association mapping by incorporating multiple traits, multiple SNPs, and pathways; (4) differential expression analysis in bisulfite sequencing, RNA sequencing or other functional genomics sequencing studies; (5) modeling and analysis of single cell sequencing data. The successful candidate will be undertaking methodological development and will have the opportunity to analyze a variety of large-scale data types. See http://www.xzlab.org for more details of recent publications.
Applicants should have, or be studying for, a PhD in biostatistics, bioinformatics, computational biology, computer science, electronic engineering, human genetics, statistics, or related quantitative discipline. A strong computational background is also required. Applicants should send a CV, a short statement of research interests, and contact information of three referees to: Xiang Zhou (734-764-5722, firstname.lastname@example.org).
Review of applications will begin immediately, and continue until the positions are filled. The University of Michigan is an equal opportunity employer. Women and minorities are encouraged to apply.
The University of Michigan offers competing salary and excellent benefits. Ann Arbor is a progressive city of about 100,000, with excellent students and a wide vareity of sports and muscal activities. The city is rated very highly in national surveys for quality of life and has the amenities of a city many times its size.