Intern, Computational Oncology at Revolution… · San…

Summary: Revolution Medicines is a late-stage clinical oncology company focused on developing targeted therapies for RAS-addicted cancers. The intern will evaluate computational strategies for analyzing tumor states from transcriptomic data, benchmarking deconvolution methods and assessing best practices in single-cell analysis. Responsibilities: - Evaluate Deconvolution Methods: - Review leading bulk and spatial deconvolution tools - Benchmark selected methods using curated datasets and single-cell references - Assess robustness in detecting immune shifts, resistant tumor states, and TME remodeling - Test Single-Cell Analysis Best Practices: - Compare normalization, integration, and batch correction strategies - Evaluate clustering robustness and annotation reproducibility - Assess the impact of different processing steps on biological interpretation Required Qualifications: - Pursuing a BS or MS in Computational Biology, Bioinformatics, Systems Biology, or related field - Proficiency in R and Python Preferred Qualifications: - Experience analyzing RNA-seq data (bulk and/or single-cell) - Experience with Seurat, Scanpy, or scVI - Familiarity with tumor microenvironment biology Required Skills: Computational Biology, Bioinformatics, Systems Biology, R, Python, RNA-seq data analysis, Single-cell RNA-seq analysis, Bulk RNA-seq analysis, Seurat, Scanpy, scVI, Tumor microenvironment biology Benefits: Competitive cash compensation, Robust equity awards, Strong benefits, Significant learning and development opportunities