Postdoctoral Fellow: Life-Course & Multi-Omics Epidemiology

Massachusetts General Hospital; Boston (MA); On-site; USD 70,000 - 72,000; Full time

Job summary

Massachusetts General Hospital is seeking a highly motivated post-doctoral fellow in the Center for Genomic Medicine to study life-course epidemiology and multi-omics integration using large-scale EHR-based biobanks and longitudinal cohorts.

The successful candidate will work under senior investigators, contribute to data analysis across omics platforms, and collaborate with Harvard Medical School and the Broad Institute. Strong programming and English communication are required.

Qualifications

• Ph.D. in epidemiology, bioinformatics, biostatistics, computational biology, or related field; degree must be completed by start date.
• Priority for candidates with population-based research experience using phenotypic and/or multi-omics data from EHR, cohort studies, and/or biobanks.
• First author of one or more peer-reviewed publications and/or conference presentations.
• Experience with omics platforms (genetics, genomics, epigenetics, metabolomics, or proteomics) or interest in such research.
• Strong programming skills in R, Python, and/or SAS; excellent English verbal and written communication.

Responsibilities

• Lead research projects including life-course epidemiology and multi-omics integration.
• Work with clinical, genetic, and multi-omic data from large-scale EHR-based biobanks and cohorts.
• Collaborate across disciplines and mentor junior researchers.
• Develop and apply analytic methods to elucidate mechanisms linking exposures to disease risk.

Skills

R

Python

SAS

Omics data analysis

English communication

Independent researcher

Education

Ph.D. in epidemiology, bioinformatics, biostatistics, computational biology, or related field

MD

Job description

Massachusetts General Hospital is seeking a highly motivated post-doctoral fellow in the Center for Genomic Medicine to study life-course epidemiology and multi-omics integration using large-scale EHR-based biobanks and longitudinal cohorts.

The successful candidate will work under senior investigators, contribute to data analysis across omics platforms, and collaborate with Harvard Medical School and the Broad Institute. Strong programming and English communication are required.