Intern, Bioinformatics
About The Position
Revolution Medicines is a clinical-stage precision oncology company focused on developing novel targeted therapies to inhibit frontier targets in RAS-addicted cancers. The company’s R&D pipeline comprises RAS(ON) Inhibitors designed to suppress diverse oncogenic variants of RAS proteins, and RAS Companion Inhibitors for use in combination treatment strategies. As a new member of the Revolution Medicines team, you will join other outstanding Revolutionaries in a tireless commitment to patients with cancers harboring mutations in the RAS signaling pathway. The Opportunity: We are seeking a highly motivated Bioinformatics Intern to support integrative analysis of single-cell datasets aimed at understanding tumor microenvironment responses to KRAS inhibitors. This role will focus on harmonizing and analyzing multi-source single-cell sequencing data to characterize treatment-induced cellular and molecular changes within tumors. The intern will work closely with computational biologists and translational scientists to generate insights that inform therapeutic strategy and combination approaches.
Requirements
- Proficiency in Python (preferred) or R for data analysis.
- Experience working with high-dimensional biological datasets.
- Familiarity with machine learning or statistical modeling.
- Strong data wrangling and preprocessing skills.
- Understanding of molecular biology and genomics concepts.
- Ability to write clean, reproducible, and well-documented code.
- Strong analytical thinking and problem-solving skills.
- Effective written and verbal communication skills.
Nice To Haves
- Experience with single-cell analysis frameworks (e.g., Scanpy, Seurat, AnnData).
- Familiarity with batch correction and dataset integration methods (e.g., Harmony, scVI, Seurat integration).
- Experience analyzing RNA-seq, ATAC-seq, or other sequencing-based assays.
- Knowledge of tumor immunology or tumor microenvironment biology.
- Experience with pathway enrichment or gene set analysis tools.
- Prior experience in cancer genomics or translational research.
- Experience working in a collaborative research environment.
Responsibilities
- Integrate multiple single-cell RNA-seq (scRNA-seq) across studies and platforms.
- Perform data preprocessing, quality control, normalization, and batch correction.
- Harmonize metadata and cell annotations across datasets.
- Conduct clustering, cell-type identification, and differential expression analyses.
- Characterize tumor microenvironment changes following KRAS inhibitor treatment, including immune infiltration shifts, myeloid reprogramming, T cell activation/exhaustion states, and stromal remodeling.
- Perform pathway enrichment and gene signature analyses.
- Generate clear visualizations.
- Develop reproducible, well-documented computational workflows.
- Present findings to cross-functional research teams.
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What This Job Offers
Career Level
Intern
Education Level
No Education Listed
