Translational Genomics / Machine Learning Research Fellow - Pochet Lab

Brigham and Women's Hospital / Harvard Medical School
Job Location
Boston, MA 02115
Job Description

The Pochet Lab ( at the Department of Neurology at the Brigham and Women’s Hospital, Harvard Medical School is currently seeking a Research Fellow in the field of translational genomics / machine learning to join our research effort in understanding the molecular and mechanistic basis of cancer, infectious, neurological and immune mediated disease.

This position offers a stimulating and multidisciplinary environment. The fellow will work as part of a team of researchers across Harvard Medical School, Brigham and Women’s Hospital as well as the Broad Institute of MIT and Harvard. He or she will join an ongoing research program that aims at the integrated analysis of multi-omics profiles from patients with multi-omics profiles from genetic and chemical perturbation studies in cell lines to translate knowledge from model systems to studies of human disease. The project will entail developing innovative computational strategies to integrate heterogeneous genomic data, thus developing powerful toolboxes for application in complex human disease. The fellow will collaborate closely with a broad network of collaborators at Harvard Medical School, Brigham and Women’s Hospital, the Broad Institute of MIT and Harvard, and Stanford University.


Applicants should have a strong computational background and expertise in dealing with very large genomic data sets. Excellent programming, data analysis and machine learning skills are required. Experience with RNA and DNA sequencing data is a major plus. The ideal candidate should be passionate about the translation of genomics into clinical practice, and be highly motivated to work in a fast-paced and highly collaborative environment.

How to Apply

Applications and inquiries should be submitted by e-mail to Dr. Nathalie Pochet ( Please include your CV, a cover letter describing previous research, research interests, and future goals, as well as 3 references.

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