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Job Summary
Summary: Collaborates with team members to assist in collecting, analyzing, and interpreting data sets.
Essential Functions-Writes and runs basic queries as needed.
-Assists in maintaining existing reporting systems.
-Contributes to presentations to key stakeholders.
-Works with senior analysts to design, maintain, and distribute reports.
-Learn leading practice analysis methodologies.
-Conduct continuous analysis of current performance and accurately forecast data trends.
Position Overview
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 a part of a world-class research community at MGH, HMS, and the Broad Institute.
Key Responsibilities
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. Specific responsibilities include:
- 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
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.
Qualifications
Required
- 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
- 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
Compensation
This is a full-time, benefits-eligible position. Salary will be based on experience, beginning at a minimum of $55,000 per year and a maximum of $60,000 per year.
Additional Job Details (if applicable)
Physical Requirements
Hybrid
100 Cambridge Street
40
Regular
Day (United States of America)
Pay Range
$53,040.00 - $75,888.80/Annual
Grade
5
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