Details Title Postdoctoral Research Position in Statistical Genetics and Genomics School Harvard T.H. Chan School of Public Health Department/Area Biostatistics Position Description Postdoctoral Research Fellow position in statistical genetics and genomics is available at the Department of Biostatistics Harvard T. H. Chan School of Public Health. This position will be supervised by Dr. Xihong Lin (https://www.hsph.harvard.edu/lin-lab/), Professor of Biostatistics and Professor of Statistics. The postdoctoral fellow will develop and apply statistical, machine learning (ML), and AI methods for analysis of large-scale whole genome genetic and genomic and phenotype data. Examples include large Whole Genome Sequencing association studies, biobanks, single-cell and CRISPR multiome data, integrative analysis of genetic and genomic data, causal mediation analysis and Mendelian Randomization, polygenic risk scores, and AI/transformer-powered analysis. We seek an individual with strong backgrounds in statistics, computing, machine learning (ML), and genetics and genomics, with a focus on large-scale genetic, genomic, and phenotype data. The work will involve both methodological research and collaboration with subject matter researchers and investigators in large NIH consortia. Basic Qualifications Ph.D. in a quantitative field, e.g., statistics or biostatistics, computer sciences, computational biology, strong research background in statistics and ML, programming, data analysis, strong genetic and genomic knowledge, as well as good written and oral communication skills. Additional Qualifications Special Instructions Please submit your cover letter, CV, research statement, and three recommendation letters alongside this application. Contact Information Daniel Cohen Contact Email dpcohen@hsph.harvard.edu Equal Opportunity Employer We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, gender identity, sexual orientation, pregnancy and pregnancy-related conditions or any other characteristic protected by law. Minimum Number of References Required 3 Maximum Number of References Allowed 4 Keywords Supplemental Questions