Senior Scientist II, Computational Chemistry

Revolution Medicines•Redwood City, CA

3d•$149,000 - $186,000•Onsite

About The Position

Revolution Medicines is a late-stage clinical oncology company developing novel targeted therapies for patients with RAS-addicted cancers. The company’s R&D pipeline comprises RAS(ON) inhibitors designed to suppress diverse oncogenic variants of RAS proteins. The company’s RAS(ON) inhibitors daraxonrasib (RMC-6236), a RAS(ON) multi-selective inhibitor; elironrasib (RMC-6291), a RAS(ON) G12C-selective inhibitor; zoldonrasib (RMC-9805), a RAS(ON) G12D-selective inhibitor; and RMC-5127, a RAS(ON) G12V-selective inhibitor, are currently in clinical development. As a new member of the Revolution Medicines team, you will join other outstanding professionals in a tireless commitment to patients with cancers harboring mutations in the RAS signaling pathway. The Opportunity: We are seeking an accomplished, independent and creative Senior Scientist II to join our Computational Chemistry team. This role offers an opportunity to provide scientific leadership across drug discovery programs, shape computational strategy, and drive the design and optimization of novel therapeutics through advanced computational, cheminformatics, and data science approaches, working at the intersection of structural biology, medicinal chemistry, biology, and data science to accelerate the development of transformative therapeutics for patients. As a key contributor in our Computational Chemistry team, you will: Serve as a computational chemistry lead on multidisciplinary discovery teams, independently shaping computational strategy, influencing project direction, and driving compound design decisions from hit finding through lead optimization. Integrate complex SAR, structural biology, biophysical, biochemical, and ADME/PK data to generate testable hypotheses, identify design opportunities, and independently drive compound prioritization strategies for Ro5 and bRo5 molecules. Act as a strategic partner to medicinal chemistry, proactively proposing compound designs, prioritization frameworks, and risk-mitigation strategies while clearly communicating scientific rationale to project teams and leadership. Design and implement virtual screening workflows leveraging both structure-based and ligand-based computational methods to discover novel hit compounds and accelerate lead optimization processes. Critically evaluate, implement, and apply advanced computational methodologies, including physics-based modeling, enhanced sampling, free energy methods to address program-specific challenges and improve decision-making. Collaborate with the Advanced Analytics team to evaluate and validate machine learning models and generative AI workflows for molecular design, ensuring the models are statistically rigorous, fit-for-purpose, and aligned with project decision-making needs. Provide innovative ideas and models to challenge and guide project roadmap while serving as lead computational chemistry representative on drug discovery pipeline projects Devise and execute strategies to augment our hit finding abilities for novel protein and protein-protein targets, aid in designing diverse chemical libraries.

Requirements

PhD in computational chemistry or related field.
5+ years of computational chemistry experience in the biotechnology/pharmaceutical industry, with a demonstrated track record of impactful contributions to drug discovery programs, including advancement of compounds, patents, publications, presentations, or key program decisions.
Expert-level knowledge of contemporary computational chemistry methods and their use in protein-ligand analysis and drug design such as docking, virtual screening, pharmacophore modeling, MD simulation, QM calculations etc.
In-depth experience with computational chemistry, cheminformatics, data science, machine learning software.
Scientific programming or scripting in Bash, Python, R, Java, C languages, or similar languages.
Excellent oral and written communication skills. Experience in positively influence team decisions and effectively collaborate across multidisciplinary environments.
Driven by a desire to be innovative and creative in a high energy, fast-paced environment.

Nice To Haves

Experience with Ro5 and bRo5 modalities, including macrocycles, molecular glues, covalent ligands, or other challenging therapeutic modalities.
Experience working in HPC/cloud environments and developing scalable computational workflows.
Strong publication history demonstrating computational chemistry expertise and innovation.
Familiarity with data visualization tools and analytics tools for effective communication of insights.

Responsibilities

Serve as a computational chemistry lead on multidisciplinary discovery teams, independently shaping computational strategy, influencing project direction, and driving compound design decisions from hit finding through lead optimization.
Integrate complex SAR, structural biology, biophysical, biochemical, and ADME/PK data to generate testable hypotheses, identify design opportunities, and independently drive compound prioritization strategies for Ro5 and bRo5 molecules.
Act as a strategic partner to medicinal chemistry, proactively proposing compound designs, prioritization frameworks, and risk-mitigation strategies while clearly communicating scientific rationale to project teams and leadership.
Design and implement virtual screening workflows leveraging both structure-based and ligand-based computational methods to discover novel hit compounds and accelerate lead optimization processes.
Critically evaluate, implement, and apply advanced computational methodologies, including physics-based modeling, enhanced sampling, free energy methods to address program-specific challenges and improve decision-making.
Collaborate with the Advanced Analytics team to evaluate and validate machine learning models and generative AI workflows for molecular design, ensuring the models are statistically rigorous, fit-for-purpose, and aligned with project decision-making needs.
Provide innovative ideas and models to challenge and guide project roadmap while serving as lead computational chemistry representative on drug discovery pipeline projects
Devise and execute strategies to augment our hit finding abilities for novel protein and protein-protein targets, aid in designing diverse chemical libraries.