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 Bayesian statistics and EM-type algorithms. 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.

Interns/RAs/Ph.D. students/Postdoc in Statistics, Machine Learning, Statistical Genetics, and Computer Science

Interns/RAs/Ph.D. students/Postdoc in statistics, applied math, machine learning, statistical genetics, and computer science are considered at merit bases year-round.