Research Associate, Department of Genome Sciences

Postdoctoral Research Associate

The Department of Genome Sciences at the University of Virginia School of Medicine is seeking a highly motivated Postdoctoral Research Associate to join the laboratory of Dr. Charles R. Farber. This position provides an opportunity to work at the forefront of computational human genetics and genomics in a collaborative and interdisciplinary research environment. The successful candidate will focus on understanding the genetic and molecular basis of complex traits and diseases, with an emphasis on osteoporosis and cardiometabolic disorders.

This is a computational position involving the development and application of statistical and computational methods to analyze large-scale human genomic and multi-omics datasets. Current research in the laboratory integrates genome-wide association studies with functional genomics, including bulk and single-cell transcriptomics, to identify causal genes, regulatory mechanisms, and networks influencing disease risk. The Research Associate will lead projects in statistical genetics, integrative genomics, and causal inference, and will work closely with experimental collaborators.

The position offers strong mentorship, opportunities for collaboration, and support for career development, including preparation of fellowship and career transition awards. Postdoctoral employment is temporary and is normally limited to an individual who has been awarded a Ph.D. or equivalent doctorate within the previous five years and who will be involved in full-time research or scholarship at the University. Employment as a Postdoctoral Research Associate is viewed as training and is preparatory for a full-time academic or research career, is supervised by a senior scholar, and allows the appointee to publish the results of his/her research or scholarship during the training period.

Minimum Qualifications:

• Ph.D. in Genetics, Computational Biology, Biostatistics, Bioinformatics, Epidemiology, Computer Science, or a related quantitative field

Preferred Qualifications:

• Experience analyzing large-scale genomic or transcriptomic datasets
• Proficiency in R
• Experience working in Linux or high-performance computing environments
• Strong communication skills
• Ability to work both independently and in collaborative settings