Mount Sinai, located in New York City, NY is seeking exceptional Assistant or Associate Professor tenure-track faculty candidates to lead ambitious data-driven genomic research programs in the Institute for Genomic Health (IGH) at the Icahn School of Medicine at Mount Sinai. IGH is led by Director Professor Eimear Kenny and Clinical Director Michael Murray.

We are on the verge of a clinical evolution that will leverage knowledge from deep databases of human genomes and clinical information from large health systems to change the practice of medicine as we know it today. The successful candidate will lead research at the interface of genomics and computer science to improve human health. The research program can span a number of different fields, including population and statistical genetics; computational and machine-learning approaches for genomics and/or electronic health record (EHR) mining; monogenic disorders or complex diseases; translating genomic information into novel therapies; and predicting genomic risk for human diseases. We seek faculty members interested in working in a fast paced, highly collaborative environment in which interdisciplinary teams of data scientists, clinician scientists, and disease area experts work together with the shared goal of leveraging large-scale data to predict, test, and translate genomic information into new paradigms for genomic health.

Faculty recruits will hold a primary appointment in IGH and a secondary appointment in the Department of Genetics and Genomic sciences (5th ranked nationally) and/or the Department of Medicine (12th ranked nationally). The appointed faculty will be embedded in an interdisciplinary team of clinicians, data scientists, and health system researchers. Current arenas of research include applying data science approaches to mine deep databases of genomic information; accelerating the pipeline for clinical genomic/polygenic risk prediction; clinical trials to integrate novel technology and/or genomic information into routine clinical care; promotion of health equity by building resources, knowledge, and best practices for genomic medicine implementation in diverse and underserved populations. Distinguishing features of our research are the full access to the BioMe biobank (a germline DNA repository of over 60,000 Mount Sinai patients linked to EHR data) and through the newly launched Mount Sinai Million Health Discoveries Program, which aims to enroll one million racially and ethnically diverse patients in the next five years. Other resources include a state-of-the-art high performance computing ecosystem, and access to genomic, multi-omic, and disease/EHR data as part of NIH-funded consortia including the eMERGE, PAGE, CSER, TOPMed, GSP, and CAAPA projects. The appointed faculty will be responsible for developing a program that applies innovative approaches to perform integrative analyses of genomic data combined with other molecular and clinical datasets to infer predictive models of biological phenotypes, and to prevent and treat disease. This position offers a unique opportunity to develop and lead genomic research using cutting edge health systems data.

Candidates should have advanced training in computational genomics, genomic research and/or genomic medicine, with a track record of innovation in a biomedical application, as evidenced by a strong publication record. Applicants should have a PhD in statistical genetics, population genetics, computer science, applied mathematics, computational biology, or another relevant quantitative scientific discipline. MD or MD/PhD candidates with computational training are also encouraged to apply.

We offer highly competitive recruitment packages, strong institutional commitments to faculty support and workforce diversity, comprehensive benefits, relocation services, and a rewarding work and life environment. The Icahn School of Medicine is located in the heart of Manhattan with offices one block from Central Park.

Review of applications will begin immediately and will remain open until positions are filled.

Tenure track candidates are expected to obtain independent funding to grow and sustain their research program.