Machine Learning Research Scientist/Senior Machine Learning Research Scientist, Structure and Simulation (AI for Drug Discovery)
Role details
Job location
Tech stack
Job description
Advances in AI, data, and computational sciences are transforming drug discovery and development. Roche's Research and Early Development organisations at Genentech (gRED) and Pharma (pRED) have demonstrated how these technologies accelerate R&D, leveraging data and novel computational models to drive impact. Seamless data sharing and access to models across gRED and pRED are essential to maximising these opportunities. The new Computational Sciences Center of Excellence (CoE) is a strategic, unified group whose goal is to harness the transformative power of data and Artificial Intelligence (AI) to assist our scientists in both pRED and gRED to deliver more innovative and transformative medicines for patients worldwide., Design and train foundation models at scale to answer challenging research questions in large-molecule drug discovery and protein engineering.
- Leverage massive structural biology and biophysical datasets, building novel architectures that capture complex geometric and physical priors.
- Contribute to publications and present scientific findings at internal and external venues.
- Solve real, pressing problems in drug discovery that enable new portfolio capabilities
In this role, as a Senior ML Scientist you will: * Design and train foundation models at scale to answer challenging research questions in large-molecule drug discovery and protein engineering.
- Leverage massive structural biology and biophysical datasets, building novel architectures that capture complex geometric and physical priors.
- Contribute to cross-functional research teams across the Computational Sciences Center of Excellence.
- Drive publications and present scientific findings at internal and external venues.
- Solve real, pressing problems in drug discovery that enable new portfolio capabilities
Requirements
PhD degree in Computational Biology, Computer Science, Chemistry, Physics or related disciplines, with up to 2 years of industry research experience (Scientist) or 2+ years of industry research experience (Senior Scientist).
- Demonstrated experience with Python and deep learning libraries such as PyTorch and/or JAX.
- Demonstrated experience architecting and training deep learning models, particularly utilizing modern approaches (e.g., multimodal representation learning, geometric deep learning, and diffusion models).
- Expertise in molecular dynamics simulations and classical force fields (e.g., AMBER, CHARMM, OpenFF), as well as hands-on experience with molecular modeling tools (e.g., OpenMM, Rosetta).
- Demonstrated research experience, including at least one first author publication (or equivalent).
- Strong communication and collaboration skills
- Public portfolio of computational projects (available on e.g. GitHub)