Description
FL117, a venture-backed stealth AI x bio company, is seeking a Sr. Scientist / Principal Scientist, Molecular Simulations. You will build the physics layer of a drug development AI platform. You will characterize how binders engage their targets and validate generated designs before they are committed to synthesis. You will work at the interface of structure-based modeling and generative ML, turning simulation output into training signals.
Responsibilities:
- Binder Characterization: Run and interpret structural and dynamic analysis of ligand–target complexes, peptides, macrocycles, nanobodies/VHHs, antibody CDRs.
- Pocket & Target Assessment: Characterize binding sites, including cryptic and induced-fit pockets, across the target portfolio using MD, enhanced sampling, and pocket detection methods.
- Design Validation: Triage generated molecules before synthesis through a combination of pose prediction and refinement, docking rescoring, binding-mode stability under MD, ligand strain and conformational ensemble analysis.
- Free Energy & Affinity Prediction: Build, validate, and own the affinity prediction workflow (relative and absolute FEP, MM-GBSA/PBSA, endpoint methods).
- Beyond-Rule-of-5 Properties: Model conformational behavior, intramolecular hydrogen bonding, chameleonicity, and membrane partitioning for macrocycles and other non-classical chemotypes.
- Simulation-to-ML Interface: Convert simulation output into structured signal for the generative platform in close partnership with the AI/ML team.
- Infrastructure & Throughput: Build reproducible, automated simulation pipelines on GPU cloud or HPC infrastructure.
- Cross-functional Partnership: Work directly with medicinal chemistry, pharmacology, and external structural biology and assay partners.
Must-have Qualifications:
- PhD in computational chemistry, biophysics, chemical physics, structural biology, or a related field.
- 4+ years of post-PhD molecular simulation experience, at least part of it in a drug discovery setting.
- Deep hands-on expertise in classical molecular dynamics: force fields and small molecule parameterization.
- Production experience with at least one enhanced sampling or free energy framework.
- Structure-based drug design fundamentals: docking and pose evaluation, pharmacophore and hot-spot analysis.
- Strong Python, with fluency in simulation toolchains and analysis stacks.
- Demonstrated ability to run simulations at scale on GPU, HPC, or cloud infrastructure through automation.
Preferred Experience:
- Peptide, macrocycle, or other beyond-Rule-of-5 simulation.
- Experienced with target classes such as: GPCRs, protein–protein interactions, transcription factors.
- Working with predicted structures and their limitations.
- ML-adjacent simulation work: machine-learned force fields and potentials.
- Workflow and infrastructure tooling: Snakemake/Nextflow, Airflow/Prefect/Dagster, Docker, AWS.
- Clear structural communication to non-specialists using PyMOL, ChimeraX, or Mol*.
The salary range for this role is $146,000 - $236,500. FL117 currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits.