Postdoctoral Fellow-MSH-32910-031

A computational postdoctoral position is available immediately in Human Genetics and electronic data mining for a faculty member’s research lab in the Department of Artificial Intelligence and Human Health, Icahn School of Medicine at Mount Sinai, New York. 

The lab focuses on determining the genetic and biological bases of complex disease by utilizing approaches from machine learning, human genetics, genetic epidemiology, statistical genetics, population genetics and computing.

Current research areas of interest include leveraging machine learning and electronic health record data mining for: (1) disease risk prediction (2) drug target prioritization (3) penetrance of clinical variants (4) genetic association analyses and (5) polygenic risk prediction.

The successful candidate will have the opportunity to work on large-scale cutting-edge sequencing, genotyping and functional data.

The successful candidate for this position will have substantial input to the specific nature of their research project but should broadly fit within both lab’s overall research goals. 

Lab members will benefit from collaborations with neighboring labs in the Charles Bronfman Institute for Personalized Medicine, Department of AIHH and GGS.

The term for this position is for one years. The position may be continued contingent on successful progress and available funding. A competitive salary, benefits and travel opportunities will be offered commensurate with experience and qualifications.

Informal inquiries are welcome via email to  ron.do@mssm.edu.

Job Qualifications:

1. Candidates should have a Ph.D., M.D. or equivalent doctorate with a strong background in human genetics, population genetics, bioinformatics, computational biology, or a related discipline.

2. Candidates should have proficiency in programming (e.g. Perl or Python) and statistical computing (e.g. R).

3. Candidates should have a strong track record of scientific productivity and/or leadership.