<p><strong><span data-contrast="auto">About the Role:</span></strong></p> <p><span data-contrast="auto">FL117</span><span data-contrast="none"><span data-ccp-charstyle="normaltextrun" data-ccp-charstyle-defn="{"ObjectId":"ac0262f4-8a9e-5820-b908-2d943c5f7113|1","ClassId":1073872969,"Properties":[201342446,"1",201342447,"5",201342448,"3",201342449,"1",469777841,"Aptos",469777842,"Arial",469777843,"ＭＳ 明朝",469777844,"Aptos",201341986,"1",469769226,"Aptos,Arial,ＭＳ 明朝",268442635,"24",469775450,"normaltextrun",201340122,"1",134233614,"true",469778129,"normaltextrun",335572020,"1",469778324,"Default Paragraph Font"]}">, a venture-backed stealth AI x bio company, </span></span><span data-contrast="auto">is seeking a </span><strong><span data-contrast="auto">Sr. Scientist / Principal Scientist, Molecular Simulations</span></strong><span data-contrast="auto">. Here you will build the physics layer of a drug development AI platform. </span><span data-contrast="none">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. </span><span data-contrast="auto">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.</span><span data-ccp-props="{"201341983":0,"335551550":6,"335551620":6,"335559739":0,"335559740":240}"> </span></p> <p><strong><span data-contrast="auto">Responsibilities:</span></strong><span data-ccp-props="{"201341983":0,"335559739":0,"335559740":240}"> </span></p> <ul> <li><strong><span data-contrast="none">Binder Characterization</span></strong><span data-contrast="none">: Run and interpret structural and dynamic analysis of ligand–target complexes peptides, macrocycles, nanobodies/VHHs, antibody CDRs.</span><span data-ccp-props="{"134233117":true,"134233118":true,"201341983":0,"335551550":6,"335551620":6,"335557856":16777215,"335559739":0,"335559740":240}"> </span></li> <li><strong><span data-contrast="none">Pocket & Target Assessment</span></strong><span data-contrast="none">: Characterize binding sites, including cryptic and induced-fit pockets, across the target portfolio using MD, enhanced sampling, and pocket detection methods. </span><span data-ccp-props="{"134233117":true,"134233118":true,"201341983":0,"335551550":6,"335551620":6,"335557856":16777215,"335559739":0,"335559740":240}"> </span></li> <li><strong><span data-contrast="none">Design Validation</span></strong><span data-contrast="none">: 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. </span><span data-ccp-props="{"134233117":true,"134233118":true,"201341983":0,"335551550":6,"335551620":6,"335557856":16777215,"335559739":0,"335559740":240}"> </span></li> <li><strong><span data-contrast="none">Free Energy & Affinity Prediction</span></strong><span data-contrast="none">: 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. </span><span data-ccp-props="{"134233117":true,"134233118":true,"201341983":0,"335551550":6,"335551620":6,"335557856":16777215,"335559739":0,"335559740":240}"> </span></li> <li><strong><span data-contrast="none">Beyond-Rule-of-5 Properties</span></strong><span data-contrast="none">: Model conformational behavior, intramolecular hydrogen bonding, chameleonicity, and membrane partitioning for macrocycles and other non-classical chemotypes to support oral property design. </span><span data-ccp-props="{"134233117":true,"134233118":true,"201341983":0,"335551550":6,"335551620":6,"335557856":16777215,"335559739":0,"335559740":240}"> </span></li> <li><strong><span data-contrast="none">Simulation-to-ML Interface</span></strong><span data-contrast="none">: Convert simulation output into structured signal for the generative platform in close partnership with the AI/ML team. </span><span data-ccp-props="{"134233117":true,"134233118":true,"201341983":0,"335551550":6,"335551620":6,"335557856":16777215,"335559739":0,"335559740":240}"> </span></li> <li><strong><span data-contrast="none">Infrastructure & Throughput</span></strong><span data-contrast="none">: 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. </span><span data-ccp-props="{"134233117":true,"134233118":true,"201341983":0,"335551550":6,"335551620":6,"335557856":16777215,"335559739":0,"335559740":240}"> </span></li> <li><strong><span data-contrast="none">Cross-functional Partnership</span></strong><span data-contrast="none">: 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 mo