Post-doctoral Research Fellow, Center for Genomic Medicine

Mass General Brigham•Boston, MA

6d•$70,000 - $71,500•Onsite

About The Position

The Center for Genomic Medicine (CGM) at Massachusetts General Hospital (MGH) and Harvard Medical School (HMS) is seeking a highly motivated post-doctoral fellow. This position is ideal for candidates interested in life-course epidemiology, integrated omics, women’s and children’s health, and chronic disease prevention. The fellow will work under the direct mentorship of Dr. Jie (Jack) Hu, focusing on how genetic, molecular, lifestyle, and environmental factors contribute to disease risk across the lifespan, with an emphasis on adverse pregnancy outcomes, cardiometabolic diseases, and neurodegenerative disorders. The role involves working with large-scale datasets, including electronic health records (EHR), biobanks, pregnancy/birth cohorts, and longitudinal cohort studies. The new hire will be appointed as a Research Fellow at MGH and Post-Doc at HMS.

Requirements

Ph.D. in epidemiology, bioinformatics, biostatistics, computational biology, or a related field, or an M.D. The degree must be completed by the fellowship start date.
Experience in conducting population-based research using phenotypic and/or multi-omics data from EHR, cohort studies, and/or biobanks.
First (or co-first) author of one or more peer-reviewed scientific publications and/or presentations at scientific conferences.
Experience in conducting research using one or more omics platforms (e.g., genetics, genomics, epigenetics, metabolomics, or proteomics), or interested in such research.
Strong programming skills in R, Python, and/or SAS.
Excellent English verbal and written communication skills.
Able to work both independently and in a collaborative and interdisciplinary research environment.

Responsibilities

Characterizing the risk of various chronic diseases among women with a history of adverse pregnancy outcomes, such as gestational diabetes and preeclampsia, using large-scale EHR-based biobanks and longitudinal cohort studies.
Elucidating the biological mechanisms linking adverse pregnancy outcomes to an increased risk of future chronic diseases later in life through integrative multi-omics approaches – including genetics, epigenetics, metabolomics, and proteomics – in large-scale population-based studies.
Identifying risk factors and underlying mechanisms related to the intergenerational transmission of chronic disease risk, including obesity and hypertension, by leveraging phenotypic and multi-omics data in pregnancy studies and birth cohorts.