Scientist I, Quantitative Systems… at Revolution… · Redwood…

Summary: Revolution Medicines is a late-stage clinical oncology company developing novel targeted therapies for patients with RAS-addicted cancers. They are seeking a Quantitative Systems Pharmacologist to develop, validate, and execute modeling projects focused on pharmacokinetics and pharmacodynamics for small molecule programs to support clinical translation and drug discovery efforts. Responsibilities: - Develop, validate, execute, and refine quantitative systems pharmacology (QSP) models, minimal physiologically based pharmacokinetic (PBPK) models, semi-mechanistic PK/PD models, and tumor growth models to support development and discovery phase projects including next-generation inhibitor design and assessment of combination potential - Propose and perform in silico simulations to answer complex mechanistic questions, create data visualizations to effectively communicate modeling results to a wide-ranging audience, and devise strategies to improve model outputs - Survey the related literature to understand key physiological and biological processes, abstract the basic mechanistic elements, identify the relevant data, and summarize assumptions to be incorporated into existing or new PBPK-QSP models - Propose new mechanistic in vitro and in vivo experiments to test model assumptions and structure. Provide in silico support for preclinical translation including clinical efficacious doses/exposure projection, potential combination dosing regimens with other cancer therapeutics - Work collaboratively with other functions to build internal infrastructure supporting data transfer and quality control - Document contributions, including assumptions, mathematical models, data analyses, and data visualizations, to be shared with other scientists or used for archival purposes Required Qualifications: - A Ph.D. in a quantitative discipline (systems pharmacology, computational biology, engineering, mathematics, physics, etc.) and 0-2 years of industry experience is desired - Strong understanding of the principles and limitations of mathematical modeling, pharmacokinetic models, pharmacodynamic models, and quantitative systems pharmacology/biology models - Proficiency in mathematical and computational methods including ordinary differential equations (ODEs), nonlinear systems, statistics, optimization, and parameter inference - Proven record developing, calibrating, and validating dynamical system models in pharmacological and biological systems - Demonstrable hands-on experience with programming languages used in scientific computing, such as MATLAB, Python, Julia, and R - Capable of working proactively and independently to deliver high–quality modeling results in a timely manner - Able to effectively communicate modeling assumptions, limitations, and simulation results to non-specialist and specialist audiences - A critical thinker and team player who can work cross-functionally with others Preferred Qualifications: - Experience with diverse dynamical system methods like ODE-based, PDE-based, nonlinear mixed effects, agent-based, Markov, Boolean, etc - Experience with integrating large data sets into QSP - Experience with agentic coding workflows such as Copilot, Cursor, Codex, and Claude Code - Experience with data-driven methods such as ML-based predictive regression models and physics-informed neural network models - Experience with modeling software such as SimBiology, NONMEM, Pheonix WinNonlin, Monolix, Simcyp designer, etc Required Skills: Quantitative systems pharmacology, Physiologically based pharmacokinetic (PBPK) modeling, Pharmacokinetic (PK) modeling, Pharmacodynamic (PD) modeling, Mathematical modeling, Ordinary differential equations (ODEs), Nonlinear systems, Statistics, Optimization, Parameter inference, Dynamical system modeling, MATLAB, Python, Julia, R, Nonlinear mixed effects modeling, Agent-based modeling, Markov modeling, Boolean modeling, Machine learning predictive regression models, Physics-informed neural network models, SimBiology, NONMEM, Phoenix WinNonlin, Monolix, Simcyp Designer Benefits: Competitive cash compensation, Robust equity awards, Strong benefits, Significant learning and development opportunities