Mingyao Li’s group in the Department of Biostatistics, Epidemiology and Informatics at the University of Pennsylvania invites applications for post-doctoral fellowships emphasizing statistical and machine learning methods development and applications of single-cell genomics techniques, including single-cell RNA-seq, single-cell ATAC-seq, and spatial transcriptomics, in various human disease studies. Our group leads single-cell studies of a variety of complex human diseases and traits, including atherosclerosis, cardiometabolic disease associated inflammatory and metabolic traits, age-related macular degeneration, and Alzheimer’s disease. Postdoctoral positions may emphasize understanding the cellular heterogeneity and the underlying molecular mechanisms of one or more of these diseases and traits, and the development of statistical and machine learning methods and software relevant to these studies. Further information about our research can be found at transgen.med.upenn.edu
Applicants should have a doctoral degree in Biostatistics, Computational Biology, Computer Science, Human Genetics, or other relevant quantitative disciplines. Experience in statistical/machine learning algorithm development and/or analysis of high-throughput genomics data is preferred. Generous salary support is available.
Applicants should send CV, one representative first/co-first author manuscript, and names of at least two references to: Mingyao Li (email@example.com).