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Principal Computational Scientist, Discovery Chemistry

Genentech -
San Francisco, CA

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Job Details

Full-time
$144,900 - $269,100 a year

Qualifications

AI models
Bioinformatics
Drug development research projects
Doctor of Computational Chemistry
Computational research
Data storage
Next generation sequencing
Computer Science
Predictive modeling analysis
Molecular dynamics simulations
Scientific publications
Automation
High-performance computing clusters
Data pipeline automation
In silico prediction
AI tools proficiency
Software implementation
Generative models
Process design
Simulation modeling (chemistry)
Application deployment
Doctoral degree in Computer Science
Programming languages
Machine intelligence
Drug discovery
Doctor of Philosophy
Model deployment
Application design
Structural modeling
Organizational skills

Full Job Description

The Position

The Opportunity

We are seeking an exceptional computational scientist to apply cutting-edge computational science, focussing on peptide therapeutic discovery. The ideal candidate will possess a unique blend of expertise in computational chemistry, including machine learning, to drive the advancement of our peptide hits to clinical candidates. This is a critical strategic role aimed at accelerating our discovery pipelines, optimizing our lead candidates, and unlocking the full potential of our experimental data.

Key Responsibilities

Advanced Modeling & Prediction: Lead the development and implementation of advanced computational methods (structure-based, physics-based) for target and peptide modeling and optimization. Implement machine learning models to accurately predict critical peptide properties such as solubility, permeability, stability, immunogenicity, and potency.
Platform Development: Contribute to the design, development, and deployment of a unified computational platform for peptide therapeutic discovery. Spearhead the creation of complex workflows and pipelines to enable the selection, design, and optimization of peptide modalities.
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, to drive progress in drug discovery with a focus on therapeutic peptide design.
Provide strategic direction and present scientific findings to internal and external stakeholders, including wet-lab scientists.
Data Infrastructure & Informatics: In collaboration with our Computational Sciences Center of Excellence, implement robust, scalable data infrastructure and automated pipelines for the efficient processing, storage, and analysis of large datasets from next-generation sequencing (NGS). Integrate proprietary data from protein crystallography, biomolecular NMR, cryo-EM, and biophysics.
Cross-Functional Collaboration: Work closely with the Peptide Therapeutics and Discovery Chemistry Departments and collaborate with multidisciplinary teams to integrate computational strategies into peptide hit discovery, hit-to-lead, and lead optimization. Foster a collaborative environment with wet-lab scientists to ensure data-driven workflows. Collaborate with computational scientists across the Drug Discovery organization and in our AI For Drug Discovery group.

Who You Are

Ph.D. in Computational Chemistry, Bioinformatics, Computer Science, or a related field.
0-6 years of relevant post-Ph.D. experience in industry or a research organization.
Proven track record of computational peptide discovery or design projects.
Deep knowledge of computational chemistry principles and general molecular modeling techniques (e.g., docking, molecular simulation, homology modeling, 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

Experience with non-canonical amino acids and their integration into peptide design.
Familiarity with computational software such as MOE, Schrodinger, OpenEye, and/or Rosetta.
Experience in AI/ML applications in the peptide space, with a focus on their application for molecular design.
Experience related to the application of cheminformatics in peptide library design.
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 California is $144,900 to $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.

Benefits

Genentech 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 FACTS

Job Sub Category

Research Biology
Schedule

Full time
Job Type

Regular
Posted Date

May 19th 2026
Job ID

202605-112433

Apply Now

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