Research Fellow – Khera Lab

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The Khera Laboratory – based within the Center for Genomic Medicine at Massachusetts General Hospital (MGH) and the Cardiovascular Disease Initiative at the Broad Institute of MIT and Harvard – is looking for an exceptional postdoctoral researcher to join our research group.


Prior work in the group has pioneered the use of ‘polygenic risk scores’ to quantify inherited susceptibility to disease, studied the interaction of genetic factors with lifestyle and environmental exposures in determining health outcomes, and identified new genetic drivers of cardiometabolic conditions. These observations have been published in leading scientific journals, including New England Journal of Medicine, JAMA, Cell, and Nature Genetics.


The successful candidate will join an interdisciplinary team of clinician-scientists, statistical geneticists, machine learning experts, genetic counselors, and data visualization experts working together to 1) use human genetics as a tool to probe disease biology; 2) integrate genetic and non-genetic factors into improved risk models; and 3) conduct implementation studies within genomic and precision medicine to confirm clinical utility.


The candidate will lead projects related to cardiovascular and other important diseases. Projects will include analysis of genomic data, clinical data from electronic medical records, and development of clinical trials to test new approaches for clinical care. The candidate must thrive in an academic/professional atmosphere, where interdisciplinary teams are central to project success.


The position is ideal for a fellow interested in a career in an innovative academic research career. Ideal candidates will train to lead and design experimental and/or computational projects that push the boundaries of human genetics and reveal the functions of genetic variants associated with heart disease. This position will prepare young researchers to become principal investigators or junior faculty members, so they also take on senior responsibilities like mentoring, grant writing, and teaching. We emphasize the research training and career development for all lab members, and the candidate will have chances to interact with the research teams within Broad Institute and also the broader community in MIT, Harvard and the Harvard-affiliated hospitals across Boston.


  • Develop study hypotheses
  • Conduct data analyses on a range of study cohorts and phenotypes, including genetic data (genotyping array, whole exome sequencing, and whole genome sequencing), imaging data (cardiac MRIs, coronary CT scans), electronic health record data, and large-scale metabolomic and proteomic data
  • Manage and integrate datasets, including facilitating cost-effective organization of data in on-prem and cloud-based storage platforms
  • Lead the interpretation of data and results
  • Regularly communicate project status updates via Slack and team meetings
  • Coordinate and interact closely with other scientists on data quality and file management
  • Actively participate in the preparation of manuscripts for publication and present at scientific conferences
  • Assist in peer- and student-mentorship, shares expertise, provides training and guidance as needed
  • Participate within a team of scientists to foster a culture of scientific excellence and collaboration


  • Sound understanding of statistics and biological concepts coupled with data science skills to collect, clean, analyze and visualize complex biological data
  • Strong analytical skills and the ability to function and communicate effectively in a highly productive multi-disciplinary environment
  • Track record of leading – or playing an important role – in prior scientific publications
  • Deep understanding of biostatistical and epidemiologic methods
  • Excellent programming skills (e.g. R, python, genomic analysis tools)
  • Experience working with genotyping and/or gene sequence data – including quality control and association analyses with clinical phenotypes
  • Outstanding communication, organization, and time management skills



  •  Not Applicable


 Minimum Required:Doctoral Degree




Doctoral Degree

Field of Study/Additional Specialized Training:

  • Ph.D. in Epidemiology, Biostatistics, Genetic Epidemiology, Statistical Genetics, or other relevant scientific discipline or equivalent experience required


Equivalent Experience:

  • Not Applicable



  • At least two years of experience working with biologic datasets – preferably large scale genetic sequencing data and clinical data – in an academic, pharmaceutical or biotech environment


Preferred Qualifications:

  • Recognized excellence as evidenced from preprints or peer-reviewed publications
  • Basic familiarity with commonly used machine learning approaches
  • Familiarity and clinical disease entities and epidemiologic approaches to study them
  • Experience in Unix and bioinformatics tools (Python, R, etc.) Familiarity with statistics/models.
  • Demonstrated experience designing computational methods and tools, including prior experience with algorithms relevant to computational biology, with particular preference for experiences involving high-dimensional data analysis.



  • Not Applicable


EEO Statement

Massachusetts General Hospital is an Equal Opportunity Employer.  By embracing diverse skills, perspectives and ideas, we choose to lead. Applications from protected veterans and individuals with disabilities are strongly encouraged.



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