Postdoctoral Research Fellow in Computational Biology

Division of Computational Biology, Department of Quantitative Health Sciences, Mayo Clinic

Mayo Clinic in Rochester, Minnesota is seeking a postdoctoral candidate with a Ph.D. in statistics/biostatistics (with statistical genetics emphasis) or psychiatric genetics. Experience with machine learning and AI methodology is preferred. The successful candidate will work with Dr. Joanna Biernacka’s team, as well as physician scientists in the Department of Psychiatry and Psychology, and other trainees and analysts, and will apply biostatistics and statistical genetic methods to studies in precision psychiatry. The group’s work includes studies of bipolar disorder and alcohol use disorder, and collaboration with multiple consortia including the PsycheMERGE network. The postdoctoral fellow will also have the opportunity to work on the development and evaluation of novel statistical methods for genomic and other biomarker studies of complex human traits.

Mayo Clinic is a world-class health care organization, with cutting-edge research programs. Scientists in the Division of Computational Biology work collaboratively with basic and clinical researchers, providing expertise in study design and data analysis and interpretation to enable discoveries with high impact on patient care. They also lead the development of statistical and informatics methodologies for analysis of biomedical data. In collaboration with the Department of Psychiatry and Psychology, members of the Division lead a well-established program in psychiatric genetics and precision psychiatry.

Minimum qualifications include a Ph.D. degree in statistics, biostatistics, epidemiology, or a closely aligned area. Excellent written and oral communication skills are required. The position is available immediately and can be either 1 or 2 years in duration, with a possibility of extension. Questions should be directed to Joanna Biernacka: [email protected].

Must have a Ph.D., M.D., or equivalent doctoral degree in a field deemed relevant by the program.