Postdoctoral Research Fellow – Khera Lab

Apply online here: https://partners.taleo.net/careersection/ghc/jobdetail.ftl?job=3158519&tz=GMT-04%3A00&tzname=America%2FNew_York

GENERAL SUMMARY/ OVERVIEW STATEMENT:
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 seeking multiple exceptional postdoctoral research fellows to join our research community.
Prior work in the group has pioneered the use of ‘polygenic 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 MedicineJAMACell, and Nature Genetics.
The research fellow will be personally mentored by Dr. Khera and join an interdisciplinary team of clinician-scientists, statistical geneticists, machine learning experts, genetic counselors, and data visualization experts working together to:
  • Use human genetics as a tool to probe disease biology
  • Integrate genetic and non-genetic factors into improved risk models
  • Conduct implementation studies within genomic and precision medicine to confirm clinical utility
The successful candidate will assist with projects related to cardiovascular and other important diseases. Representative examples of high-priority projects and collaborations include:
  • Improving the transethnic portability of polygenic scores, making use of public and private datasets as a site for a large NHGRI Consortium led by Dr. Khera
  • Use of machine learning on raw imaging data to develop and understand features important for cardiometabolic diseases, such as local fat depots (and latent representations thereof) in collaboration with the Broad’s Machine Learning for Health group and the new Eric and Wendy Schmidt Center
  • Rare variant analyses for cardiometabolic traits to identify molecular subtypes of common diseases and – in cases of protection from disease – directly inspire a therapeutic strategy
  • Understand the role of genetics in both disease onset, but also progression, with an eye towards informing clinical trial design, including participation in the Chronic Liver Disease Genetics Consortium led by Dr. Khera in collaborations focused on fatty liver disease and steatohepatitis with MGH and UC San Diego
The position is ideal for a fellow interested in a career in an innovative academic research center. Ideal candidates will train to lead and design 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 opportunities for all lab members, and the candidate will have chances to interact with the research teams within the Center for Genomic Medicine at MGH, Broad Institute and also the broader community in MIT, Harvard and the Harvard-affiliated hospitals across Boston.

 

PRINCIPAL DUTIES AND RESPONSIBILITIES:
  • Explore study hypotheses and assist PI and laboratory research team to design and analyze results
  • 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
  • Assist in integrating datasets, including facilitating cost-effective organization of data in on-prem and cloud-based storage platforms
  • Implement the design and development of statistical analysis plans for projects
  • Regularly communicate project status updates via Slack and team meetings; Collaborate closely with team to ensure activities are within scope, timeline of project goals and ensure analytical goals are achieved
  • Participate in writing progress reports and grant proposals for funding agencies
  • Participate within a team of scientists to foster a culture of scientific excellence and collaboration
  • Actively participate in the preparation of manuscripts for publication and present at scientific conferences
  • Coordinate and interact closely with other scientists on data quality and file management
  • Assist in peer- and student-mentorship, shares expertise, provides training and guidance as needed
 

SKILLS/ABILITIES/COMPETENCIES REQUIRED:

  • 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
  • Strong record of productivity, motivation, and adaptability
  • Knowledge of cardiovascular disease is not required

EDUCATION:

  • Minimum Required: 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

EXPERIENCE:

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

PREFERRED QUALIFICATIONS:

  • Ability to independently conduct hypothesis-driven research
  • Prior experience in human genetic analyses and bioinformatics analyses of publicly available datasets
  • Experience with cloud computing is strongly preferred
  • Familiarity with clinical trial concepts
  • Recognized excellence as evidenced from preprints or peer-reviewed publications
  • 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
  • Basic familiarity with commonly used machine learning approaches
  • Experience in Unix and bioinformatics tools (Python, R, etc.) Familiarity with statistics/models
  • Familiarity and clinical disease entities and epidemiologic approaches to study them

LICENSES, CERTIFICATIONS, and/or REGISTRATIONS:

  • Not Applicable

SUPERVISORY RESPONSIBILITY (authority to hire, promote, or terminate: 

  • 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.
 
Apply online here: https://partners.taleo.net/careersection/ghc/jobdetail.ftl?job=3158519&tz=GMT-04%3A00&tzname=America%2FNew_York