Take responsibility for small molecule binding free energy calculations that feed directly into project decision making
Define best practice protocols across programs, and evolve them as the platform improves
Optimize and improve existing methods, not just run them
Start from existing methods and code bases (for example FEP, TI, and related alchemical / free energy workflows) and improve them for both speed and accuracy
Identify and implement tricks and approximations from the free energy literature that move us along the “fast and accurate enough” tradeoff curve
Help determine where more physics is needed and where we can safely approximate
Build tools, not just papers
Design, implement, and maintain free energy workflows and utilities that other scientists at Genesis can actually use
Contribute production quality code, tests, and documentation
Work with ML researchers and platform engineers to plug your methods into GEMS, our internal platform for molecular generation, and as well as our internal benchmarking suites
Partner with ML, CADD, and medicinal chemistry
Collaborate with ML researchers to combine data driven models with physics based methods, especially at the high potency end where physics is “the only game in town”
Work with CADD and medicinal chemists to interpret free energy results and refine design hypotheses
Help teams reason about convergence, error bars, and when to trust (or not trust) free energy outputs in real drug programs
Drive impact within the first 90 days
Quickly get hands on with our existing free energy related workflows and code.
Propose and execute concrete improvements that shorten turnaround time, improve ranking at the top of the potency range, or make the tools easier to use for project teams.
Start to define a roadmap for free energy at Genesis, including platform wide improvements and project specific ideas.
Requirements
Experience with drug discovery or platform methods development.
Strong track record in binding free energy method development for small molecules (for example FEP, TI, alchemical methods, QM/MM free energies, related approaches).
Evidence that you have built a method or tool that others actually use: open source contributions, internal platforms, or widely used workflows.
PhD in computational chemistry, theoretical chemistry, biophysics, chemical physics, or a related field, or equivalent experience.
Proficiency in Python is a requirement, while experience with a compiled language (C, C++, Fortran, or similar) is a plus.
Experience with modern software development best practices, especially git and test driven development.
Comfortable diving into existing code, understanding design choices, and making careful modifications rather than always starting from scratch.
Experience integrating methods with MD engines and workflow tools (for example OpenMM, GROMACS, NAMD, OpenFE, or similar ecosystems).
Tech Stack
Open Source
Python
Benefits
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