Job Description
Mass General Brigham relies on a wide range of professionals, including doctors, nurses, business people, tech experts, researchers, and systems analysts to advance our mission. As a not-for-profit, we support patient care, research, teaching, and community service, striving to provide exceptional care. We believe that high-performing teams drive groundbreaking medical discoveries and invite all applicants to join us and experience what it means to be part of Mass General Brigham.
Job Summary
The Bhupathiraju Lab at Channing Division of Network Medicine (Department of Medicine, Mass General Brigham) is seeking a part-time Research Assistant to support an NIH-funded project investigating metabolomic signatures of flavonoid rich foods and their relationships with type 2 diabetes.The Research Assistant will work under the supervision of Dr. Bhupathiraju and will focus on high-dimensional data analysis of metabolomics and dietary datasets using R and Python. This position is well suited for a quantitatively oriented candidate interested in metabolomics, nutritional epidemiology, and data science.
Qualifications
Principal Duties and Responsibilities
- Import, clean, and manage large, high-dimensional datasets, including metabolomic profiles, dietary intake, and clinical covariates.
- Conduct statistical and multivariable analyses in R and/or Python, including:
- Data preprocessing and normalization of metabolomics data
- Dimension reduction (e.g., PCA) and clustering methods
- Regression and other modeling approaches to relate diet to metabolomic patterns and cardiometabolic outcomes.
- Create reproducible analysis pipelines and documentation (R scripts, Python notebooks, Git/GitHub version control).
- Generate tables, figures, and visualizations for abstracts, manuscripts, and presentations.
- Assist with interpretation of findings and drafting of analytic and methods sections.
- Participate in regular lab and project meetings; present interim analyses as needed.
- Adhere to all Mass General Brigham policies regarding data security, privacy, and research compliance (including IRB requirements and HIPAA).
- Perform other related duties as assigned.
Qualifications
Required:
- Bachelor’s degree in Biostatistics, Epidemiology, Data Science, Computer Science, Bioinformatics, Nutrition, or a related quantitative field; or current enrollment in a MPH program.
- Demonstrated experience working with high-dimensional or large epidemiologic data.
- Proficiency in R and/or Python for data management, statistical analysis, and visualization.
- Working knowledge of machine learning methods
- Strong organizational skills, attention to detail, and ability to work both independently and as part of a team.
- Excellent written and oral communication skills.
Preferred:
- Prior experience with metabolomics or other omics data (e.g., genomics, proteomics).
- Experience with R packages such as tidyverse, data.table, lme4, survival, glmnet, or Python libraries such as pandas, numpy, scikit-learn, and statsmodels.
- Familiarity with dietary assessment data (e.g., FFQs, 24-hour recalls) and/or nutritional epidemiology.
- Experience with reproducible research tools (R Markdown, Quarto, Jupyter, Git/GitHub).
- Experience contributing to scientific manuscripts or conference abstracts.
Working Conditions
- Part-time position (~10–20 hours/week); schedule can be arranged within standard weekday hours by mutual agreement with the PI.
- Work may be hybrid.
Additional Job Details (if applicable)
Remote Type
Work Location
Scheduled Weekly Hours
Employee Type
Work Shift
Pay Range
$21.00 - $29.01/Hourly
Grade
5
EEO Statement:
Mass General Brigham Competency Framework
At Mass General Brigham, our competency framework defines what effective leadership “looks like” by specifying which behaviors are most critical for successful performance at each job level. The framework is comprised of ten competencies (half People-Focused, half Performance-Focused) and are defined by observable and measurable skills and behaviors that contribute to workplace effectiveness and career success. These competencies are used to evaluate performance, make hiring decisions, identify development needs, mobilize employees across our system, and establish a strong talent pipeline.
