About the job
Join Revolution Medicines, a pioneering clinical-stage precision oncology firm dedicated to crafting innovative targeted therapies that effectively combat RAS-addicted cancers. Our robust R&D pipeline includes RAS(ON) Inhibitors aimed at neutralizing various oncogenic RAS protein variants, alongside RAS Companion Inhibitors engineered for synergistic treatment approaches. As a valued member of the Revolution Medicines team, you will collaborate with exceptional colleagues who share an unwavering commitment to patients facing cancers associated with mutations in the RAS signaling pathway.
Your Role:
We are on the lookout for a driven summer intern to assess computational methodologies for deciphering tumor and tumor microenvironment (TME) states utilizing bulk, single-cell, and spatial transcriptomic data within the realm of oncology. This initiative will emphasize benchmarking deconvolution techniques and evaluating best practices in single-cell analysis to identify the most biologically accurate and reproducible methods for examining treatment responses and resistance to targeted therapies, particularly RAS(ON) inhibitors.
Evaluate Deconvolution Techniques:
Examine 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 Best Practices in Single-Cell Analysis:
Compare normalization, integration, and batch correction strategies.
Evaluate clustering robustness and annotation reproducibility.
Assess the impact of varying processing steps on biological interpretation.