Computational Research Associate

Dr. Kenneth Westerman is recruiting a Computational Research Associate to join his interdisciplinary research group at Massachusetts General Hospital (MGH) and Harvard Medical School (HMS). The associate will contribute to cutting-edge genetic epidemiology analyses in large biobank and cohort datasets, with implications for precision medicine and cardiometabolic disease prevention. The position will be co-supervised by Dr. Arun Durvasula at the University of Southern California (USC). This is an excellent opportunity for a motivated early-career researcher to develop advanced computational skills, build a strong publication record, and be part of a world-class research community at MGH, HMS, and the Broad Institute.

About the role

Collaborates with team members to assist in collecting, analyzing, and interpreting data sets. The associate will work with Dr. Westerman to investigate genetic factors modifying the relationship between non-genetic exposures (such as adiposity and age) and cardiometabolic risk factors.

Responsibilities

• Conducting gene-environment interaction analyses in large-scale biobank and cohort datasets
• Harmonizing heterogeneous datasets including socioeconomic and lifestyle covariates and cardiometabolic trait phenotypes
• Contributing to the preparation of scientific manuscripts and presenting findings at internal group meetings and external conferences
• Collaborating with an interdisciplinary team spanning computational scientists and clinician-researchers across USC, MGH, HMS, and the Broad Institute
• Writing and running basic queries as needed
• Assisting in maintaining existing reporting systems
• Contributing to presentations to key stakeholders
• Working with senior analysts to design, maintain, and distribute reports
• Learning leading practice analysis methodologies
• Conducting continuous analysis of current performance and accurately forecasting data trends

Beyond this primary focus, there are opportunities to become involved with projects from our broader portfolio including polygenic risk scores, multi-omics analysis, and classical epidemiology in large cohort datasets.

Requirements

• Bachelor’s or master’s degree in genetic epidemiology, computational biology, bioinformatics, statistics, or a related field
• Strong programming skills in R and/or Python and comfort with Linux/shell scripting
• Excellent written and verbal communication skills
• Highly self-motivated and driven to contribute to scientific research

Preferred Qualifications

• Experience with biomedical cloud computing environments (e.g., Terra, DNAnexus) and large-scale genomic datasets (e.g., UK Biobank)
• Experience with genome-wide association studies and gene-environment interaction analysis
• Background and interest in cardiometabolic disease biology

Benefits

This is a full-time, benefits-eligible position.

Pay

Salary will be based on experience, beginning at a minimum of $55,000 per year and a maximum of $60,000 per year. The pay range for this role is $53,040.00 - $75,888.80 annually.

Schedule

• Full-time, regular employee type
• Scheduled weekly hours: 40
• Work shift: Day (United States of America)
• Hybrid work location: 100 Cambridge Street