Postdoctoral fellow

Icahn School of Medicine at Mount Sinai
Job Location
New York, NY 10029
Job Description


Open Post-Doc Position in Dr. Ron Do Lab

A computational postdoctoral position is available immediately in Statistical Genetics and/or Population Genetics in Dr. Ron Do’s lab. The Do lab is in the Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York and is situated in the Charles Bronfman Institute for Personalized Medicine.

Dr. Do’s lab focuses on determining the genetic and biological bases of complex disease. The group pursues these interests by utilizing approaches from statistical genetics, population genetics, human genetics and genetic epidemiology.

Current lab research areas include: (1) Causal inference of biomarkers with complex disease; (2) Identification of biological processes of complex disease using functional data; (3) Testing for natural selection in medically relevant loci; (4) Rare variant association studies using sequencing data; (5) data mining in electronic health records.

The successful candidate will have the opportunity to work on large-scale cutting-edge sequencing, genotyping (including Mount Sinai’s BioMe Biobank) and high-throughput functional data. Importantly, the candidate will have substantial input to the specific nature of their research project but should broadly fit within the lab’s overall research goals.

Lab members will benefit from collaborations with neighboring labs in the Charles Bronfman Institute for Personalized Medicine, the Center for Statistical Genetics, and the Icahn Institute for Genomics and Multiscale Biology. 

The term for this position is for 2-3 years with possibility of an extension depending on successful progress and available funding. A competitive salary, benefits and travel opportunities will be offered commensurate with experience and qualifications.


1. Candidates should have a Ph.D., M.D. or equivalent doctorate in statistical genetics, population genetics, computational biology and/or human genetics

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

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


Students whose classmates are interested in science are more likely to think about a career in science, technology, engineering, and mathematics, a new study says.

CNBC reports that the genetic counseling field is expected to grow as personalized medicine becomes more common.

Gladys Kong writes at Fortune that her STEM background has helped her as a CEO.

Social scientists report that the image of the 'lone scientist' might be deterring US students from STEM careers.