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Analyzing links between Dietary Fatty Acids and B-cell Lymphoma Risk

Columbia University

Eligibility

Undergraduate Only

Accepts Applications Until

Dec 20, 2025

Project Duration

Flexible

Description

Ferroptosis is a unique form of regulated cell death closely linked to lipid metabolism. Our preliminary data suggest that B-cell lymphomas are particularly sensitive to ferroptosis triggered by saturated fatty acids (SFAs). To expand upon these findings, we aim to analyze large-scale clinical datasets, such as UK Biobank and European Prospective Investigation into Cancer and Nutrition (EPIC), and conduct prospective studies to investigate potential associations between dietary intake of SFAs and B-cell lymphomas incidence.

Mentored Research Experience: This experience is ideal for a self-motivated undergraduate with a strong interest in applying statistical and computational skills to real-world biomedical questions. The student will take an active role in analyzing large epidemiological datasets to explore associations between dietary SFA intake and B-cell lymphoma risk. With guidance from faculty in the Statistics Department and a PhD student in the Stockwell lab, the student will participate in the research project, formulating hypotheses, performing statistical analyses, and interpreting findings. We’re especially looking for someone who’s excited to learn and able to make progress independently on well-defined tasks.

Research Activities:

Preprocess and analyze large-scale public datasets
Conduct statistical analyses
Generate summary tables and figures for interpretation
Attend regular check-ins to discuss results and progress

Learning Outcomes:
Hands-on research experience working with biomedical datasets
Exposure to interdisciplinary research at the intersection of statistics, biology, and medicine
Potential for authorship on future publications or presentations

Required Skills

Qualifications: Rising Sophomore or Junior preferred Major in Statistics, Mathematics, Computer Science, or related field Experience with R or Python is strongly preferred Interest in biology, cancer, or public health is a plus Strong attention to detail and willingness to learn

Additional Information

Hours per week: 8-10 hours per week during the semester/summer, with flexible scheduling

Compensation

Other

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