Research Associate at HHL Leipzig Graduate School focusing on economic psychology and leadership. Engaging in research projects while supporting teaching and supervising students' theses.
About the role
- Binding free energy specialist developing and optimizing methods to enhance drug discovery. Collaborating with teams to drive project decisions and improve existing workflows.
Responsibilities
- Own the binding free energy function
- 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).
Benefits
- We are proud to be an inclusive workplace and an Equal Opportunity Employer.
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
Senior Research Scientist focusing on quantum algorithms, driving near - term quantum advantage. Working on cutting - edge applications in a multidisciplinary environment.
Staff/Senior Research Scientist driving development of AI frontier benchmarks and datasets at Snorkel AI. Collaborating across teams to scale production and impact research community.
Research Scientist focusing on reinforcement learning for training large language models at Snorkel AI. Collaborating with research and engineering teams to advance RL data capabilities.
Research Scientist conducting original research in AI and machine learning for Spotify's Personalization team. Developing methodologies and collaborating with partners to advance personalization systems.
Research Scientist at Valence Labs developing ML models for predicting cellular responses in drug discovery. Building generative models based on massive multiomics datasets with collaborative research.
Research Assistant responsible for statistical data analysis under a Principal Investigator for health science projects. Involves data management, statistical analyses, and documentation of workflows.
Temporary Research Assistant supporting data collection for Medical Ethics at University of Pennsylvania. Engaging in programming activities and organizing research - related documentation.
Machine Learning Research Scientist conducting applied AI/ML research at SEI. Developing prototype capabilities for government workflows with a focus on mission context.
Summer Research Assistant helping with research and field work in agroforestry systems. Collecting data and assisting in various tasks based in Wisconsin.