Job Description
Well-funded biotech in SSF seeks a Computational Chemistry Director or Associate Director with experience in CADD- and structure-based design for lead optimization of small molecules to advance the pipeline of innovative therapeutics toward the clinic.
- Onsite in South San Francisco Monday through Friday (5 days / week)
Highlights :
Reports to SVP, DiscoveryPotential to have one or more direct reportsTwo lead targets : CNS oncology + neurodegenerationFinancial runway forecasted through Spring 2027~25 full-time employeesResponsibilities :
Provide strategic leadership and hands-on execution of our CADD effortsCollaborate closely with chemists and biologists on virtual screening, hit identification and structure-based designGuide the optimization of drug candidates that induce protein degradationUse machine-learning (ML) to build in silica models to predict DMPK propertiesPerform and automate high throughput molecular dynamics simulations to predict protein function and protein-ligand bindingUtilize established tools and design new methods / toolsScientific programming as neededRequired Qualifications :
PhD in Computational Chemistry or related discipline7+ years of relevant experience in drug discoveryComputer aided drug design (CADD) / structure- and ligand-based design for small moleculesDotmatics, Schrodinger, MOE, OpenEye, or Gaussian softwareQSAR, QSPR, and conformational analysisMolecular mechanics and dynamics simulationsPreferred Skills & Knowledge :
Understanding of in vitro and in vivo DMPK principlesArtificial Intelligence / Machine Learning (AI / ML) approaches to predictive modelingQuantum mechanics methodsStatistical design of experiments (DoE)Multiparameter optimizationExperimental assay methods and technology for protein-ligand interactionsProgramming with languages such as perl, python, or C++Cheminformatics / database algorithmsEmerging drug modalities such as covalent inhibitors, bifunctionals, molecular glues and / or PROTACs