Bioinformatics Analyst / Data Scientist

Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai
Job Location
1468 Madison Avenue
New York, NY 10029

A competitive salary, benefits and travel opportunities will be offered commensurate with experience and qualifications.

Job Description

A computational data scientist / bioinformatics analyst is available immediately in Dr. Ron Do’s lab. The Do lab is in the Charles Bronfman Institute for Personalized Medicine, Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York. 

A key resource of the Charles Bronfman Institute for Personalized Medicine is the electronic health record (EHR)-linked BioMe Biobank, which is comprised of more than 45,000 individuals of diverse ancestries recruited in and round New York City. BioMe currently has whole exome sequencing data (N~34,000) and genome-wide array genotyping (N~34,000) that is linked to a diverse array of medical phenotypes from the EHR.

Dr. Do’s lab focuses on determining the genetic and biological bases of human complex disease. The group pursues these interests by utilizing approaches from statistical genetics, population genetics, human genetics, 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) Inferring the strength and mode of natural selection for complex disease; (4) Rare variant association studies using sequencing data; (5) Data mining in electronic health records.

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

The term for this position is for 2 years with possibility of an extension depending on successful progress and available funding.


Candidates should have a Ph.D., or equivalent doctorate in Bioinformatics, Computer Science, Statistics, Human Genetics, Statistical Genetics, Population Genetics, or a related discipline.

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

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

How to Apply

Please send inquiries via email to (at)

Informal inquiries are welcome.

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