Strength Through Diversity
Ground breaking science. Advancing medicine. Healing made personal.
We are seeking to strengthen our analytical team in the Charles Bronfman Institute for Personalized Medicine (CBIPM) at the Icahn School of Medicine at Mount Sinai, with an outstanding computational research scientist interested in the genetics and genomics of complex traits.
We are an interdisciplinary institute with a mission to advance personalized health and health care. One of the institute’s key resources is the BioMe electronic health record (EHR)-linked Biobank, an ancestrally diverse population of >50,000 individuals recruited from throughout New York City. BioMe has a longitudinal design and captures and full spectrum of common and rare biomedical phenotypes. BioMe is also rich in genetic data, including genome-wide array genotypes, and exome (N ~34,000) and whole genome (N ~15,000) sequencing data.
The successful candidate will manage the challenges of EHR-linked data, apply phenotypic algorithms and efficiently analyze and interpret the results. This will involve the application of variant calling and annotation software to high‐density genotyping and sequencing data (including genome‐wide arrays, ExomeChip, and next generation sequencing), as well as the application and development of approaches aimed at streamlining pipelines to deal with the analyses and interpretation of data from genetically diverse populations. S/he will integrate the increasing amount of data for further downstream analyses.
The successful candidate will be part of a stimulating and internationally competitive scientific environment, and is expected to work closely with colleagues in CBIPM and with faculty from other research institutes at Mount Sinai.
- Masters degree in Computer Science,Statistics/Bioinformatics/statistical genetics/genetic epidemiology/computational biology or a related discipline is required. A Ph.D in any of these disciplines is a plus.
- An understanding of biology, particularly genetics, is advantageous.
- He or she will have excellent programming, database and interactive web application skills (e.g. Perl, Python, SQL, R Studio, R Shiny) and proven experience in the manipulation and statistical analysis (e.g. R) of large datasets from different sources and in different formats, and in conducting and organizing research projects.