Overview
Senior Machine Learning Scientist, AI for Drug Discovery (Structure, Scoring, and Simulation) – Prescient Design, within Roche Genentech Research and Early Development (gRED) and Pharma (pRED).
Advances in AI, data, and computational sciences are transforming drug discovery and development. The Computational Sciences Center of Excellence (CoE) aims to harness data and AI to assist scientists in delivering more innovative medicines for patients worldwide.
The Opportunity: We are looking for talented Machine Learning Scientists to join Prescient Design, a division devoted to developing structural and machine learning methods for molecular design. The successful candidate will design, develop, and deploy new techniques for ML-based molecular optimization for the analysis and design of small and large molecule drugs within target-driven design campaigns. Candidates may work with molecular simulation, property prediction based on sequence and/or 2D/3D structure, guided generation, cofolding, ranking, target/pocket/epitope assessment, or de novo design.
Responsibilities
* Join Prescient Design within the Computational Sciences organization in gRED. Collaborate with machine learning scientists, engineers, computational chemists, and computational biologists.
* Closely collaborate with scientists within Prescient and across gRED.
* Develop machine learning and computational workflows to analyze existing, and design new, small and large molecules.
* Form close working relationships with small molecule and protein therapeutic development efforts across the gRED organization.
* Work on existing projects and generate new project ideas.
Who You Are
* PhD degree in a quantitative field (e.g., Computer Science, Chemistry, Chemical Engineering, Computational Biology, Physics, or equivalent), or MS degree with 3+ years of industry experience.
* Demonstrated experience with machine learning libraries in production-ready workflows (e.g., PyTorch + Lightning + Weights & Biases).
* Record of achievement, including at least one high-impact first-author publication or equivalent.
* Excellent written, visual, and oral communication and collaboration skills.
Additional Desired Skills
* Experience with physical modeling methods (e.g., molecular dynamics) and cheminformatics toolkits (e.g., RDKit).
* Focus on one or more areas: molecular property prediction, computational chemistry, de novo drug design, medicinal chemistry, small molecule design, self-supervised learning, geometric deep learning, Bayesian optimization, probabilistic modeling, or related statistical methods.
* Public portfolio of computational projects (e.g., GitHub).
Location, Relocation & Compensation
This opportunity needs to be based in South San Francisco, New York City, or Basel. Relocation benefits are available. The expected salary range is $167,400 – $310,800, based on location and experience. A discretionary annual bonus may be available. Benefits are described in the provided link.
Benefits
Genentech is an equal opportunity employer. We prohibit unlawful discrimination and are committed to merit, qualifications, and competence. Accommodation requests can be made via the Accommodations for Applicants form if needed.
If you would like to explore more about the role and team, please apply through the Roche Genentech careers portal.
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