Positions
Postdoctoral Fellows in Statistical Genetics
My current research is primarily focused on the development of statistical methods for the analysis of large-scale genetic and genomic data. My recent work includes causal inference using GWAS summary-level data, clustering and deconvolution methods of spatial transcriptomic, integration of omics summary data, and deep learning methods with applications in genetic/genomics studies.
Ideal candidates should have good training in statistics and/or machine learning with good knowledge of linear mixed models, convex optimization, and Bayesian variable selection. A strong computational skill is required.
Applicants should send a CV, a short research statement, and the names of three referees to me. Review of applications will begin immediately and continue until the positions are filled.
Intern/RA in Statistics, Machine Learning, Statistical Genetics, and Computer Science
Interns in statistics, machine learning, statistical genetics, and computer science are considered at merit bases year-round.