A Postdoctoral Scholar Research Associate position in genetic epidemiology and quantitative genomics is available at the USC Center for Genetic Epidemiology in the Department of Population and Public Health Sciences. The postdoctoral fellow will work directly with Dr. Kelsey Johnson on the statistical analysis of genetic and genomic data from studies of human milk, lactation, and infant and maternal health. See our lab website for more details.
Candidates should have a Ph.D. (or equivalent qualification) in human genetics, epidemiology, biostatistics, computer science, bioinformatics, computational biology, or a related field. Proficiency in one or more programming languages (e.g. R, python, etc.) is required and proficiency in a Unix-based computing environment is preferred. Experience in analyzing biobank-scale genetic data and/or multiomic datasets is a plus.
Interested candidates should send a CV and cover letter to Dr. Johnson at kelsey.johnson@med.usc.edu. Applicants are also encouraged to reach out for any informal inquiries.
The position duration is a minimum of two years, renewed annually, and is extendable upon performance. We offer a competitive salary starting above the NIH postdoc baseline and are open to flexible start dates.
The annual base salary range for this position is $70,304 - $71,000. When extending an offer of employment, the University of Southern California considers factors such as (but not limited to) the scope and responsibilities of the position, the candidate's work experience, education/training, key skills, internal peer equity, federal, state, and local laws, contractual stipulations, grant funding, as well as external market and organizational considerations.
Candidates should have a Ph.D. (or equivalent qualification) in human genetics, epidemiology, biostatistics, computer science, bioinformatics, computational biology, or a related field. Proficiency in one or more programming languages (e.g. R, python, etc.) is required and proficiency in a Unix-based computing environment is preferred. Experience in analyzing biobank-scale genetic data and/or multiomic datasets is a plus.
