Senior​/Principal Scientist, Molecular Simulations

FL117, a venture-backed stealth AI x bio company, is seeking a Sr. Scientist / Principal Scientist, Molecular Simulations. Here 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.

We are looking for a hands‑on simulation scientist who is comfortable owning a method end to end in a cross‑functional, fast‑moving team.

• 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, and define the criteria by which a design advances or gets killed.
• Free Energy & Affinity Prediction :
  Build, validate, and own the affinity prediction workflow (relative and absolute FEP, MM-GBSA/PBSA, endpoint methods); establish its accuracy and applicability domain against measured data and report both honestly.
• Beyond-Rule-of-5 Properties :
  Model conformational behavior, intramolecular hydrogen bonding, chameleonicity, and membrane partitioning for macrocycles and other non‑classical chemo types to support oral property design.
• 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; own system setup, parameterization, QC, and analysis at portfolio scale rather than one system at a time.
• Cross‑functional Partnership :
  Work directly with medicinal chemistry, pharmacology, and external structural biology and assay partners; turn structural hypotheses into testable designs, feed returning data back into corrected models, and flag clearly where predictions are unreliable.

• PhD in computational chemistry, biophysics, chemical physics, structural biology, or a related field; MSc with equivalent industry depth considered
• 4+ years of post‑PhD molecular simulation experience, at least part of it in a drug discovery setting (Sr. Scientist); 6+ years with demonstrated ownership of a method or platform (Principal)
• Deep hands‑on expertise in classical molecular dynamics: force fields and small molecule parameterization (AMBER/CHARMM/OPLS, GAFF/OpenFF), solvation and ion treatment, equilibration protocols, and the characteristic failure modes of each.
• Production experience with at least one enhanced sampling or free energy framework (relative or absolute FEP/TI, meta dynamics, umbrella sampling, replica exchange, or weighted‑ensemble MD) including validation against measured affinities.
• Structure‑based drug design fundamentals: docking and pose evaluation, pharmacophore and hot‑spot analysis, and critical assessment of experimental and predicted structures.
• Strong Python, with fluency in simulation tool chains (OpenMM, GROMACS, AMBER, NAMD, or Desmond) and analysis stacks (MD Analysis/MDTraj, RDKit); version control and reproducible workflows as habit, not aspiration.
• Demonstrated ability to run simulations at scale on GPU, HPC, or cloud infrastructure through automation rather than manual per‑system setup.
• Judgment…