The PositionA healthier future. It’s what drives us to innovate. To continuously advance science and ensure everyone has access to the healthcare they need today and for generations to come. Creating a world where we all have more time with the people we love. That’s what makes us Genentech!The OpportunityWe are seeking an exceptional computational chemist to apply cutting-edge computational science, with an emphasis on induced proximity small molecule discovery. The ideal candidate will possess expertise in computational chemistry, collaborating within project teams to discover and advance induced proximity small molecules into clinical candidates. This is a critical role aimed at accelerating our discovery pipeline, optimizing lead candidates, and applying state of the art computational methods.Key Responsibilities:Advanced Modeling & Prediction: Lead the development and implementation of advanced computational methods, including molecular dynamics and affinity prediction, for ternary complex modeling, ligand discovery, validation and optimization. AI/ML for Drug Discovery: In collaboration with our internal AI for Drug Discovery team, apply advanced AI/ML technologies, including protein-ligand co-folding, generative and active learning models.Provide strategic direction and present scientific findings to internal and external stakeholders and project teams, including wet-lab scientists.Cross-Functional Collaboration: Work closely with Structural Biology, Biochemical Pharmacology, DMPK, Safety/Investigational Toxicity, and other groups. Foster a collaborative environment within project teams to ensure computationally informed and driven decisions. Collaborate with computational scientists across the Drug Discovery organization and in our AI For Drug Discovery group.Who You ArePh.D. in Computational Chemistry, Biophysics, or a related field.0-6 years of relevant post-Ph.D. experience in industry or a research organization.Proven track record of induced proximity discovery or design projects.Deep knowledge of computational chemistry principles and general molecular modeling techniques (e.g., docking, molecular simulation and dynamics, quantum mechanics, ligand- and structure-based design).Proficient in Python or other relevant programming languages.Experience with cloud computing platforms and/or high-performance computing (HPC) environments.Excellent communication and presentation skills, with the ability to convey complex technical concepts to diverse audiences.Ability to work productively and collaboratively in an interdisciplinary fast-paced team environment.Preferred Familiarity with computational software such as MOE, Schrodinger, OpenEye, and/or Rosetta.Experience in AI/ML applications in the induced proximity space.A strong track record of publication in leading scientific journals and presentations at major conferences.Relocation benefits are available for this job posting.The expected salary range for this position based on the primary location of South San Francisco, CA is $144,900 - 269,100. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance. This position also qualifies for the benefits detailed at the link provided below.BenefitsGenentech is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company's policy prohibits unlawful discrimination, including but not limited to, discrimination on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws.If you have a disability and need an accommodation in relation to the online application process, please contact us by completing this form Accommodations for Applicants.Job SummaryJob number: 202607-117707Date posted : 2026-07-07Profession: Research & DevelopmentEmployment type: Full time
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