2026 Summer Intern - gCS AIDD

Roche • South San Francisco, CA

2d • Onsite

About The Position

2026 Summer Intern - gCS AIDD Department Summary Prescient Design is seeking exceptional graduate interns with strong research experience in machine learning (ML) and a passion for applying advanced algorithms to scientific discovery. Our team develops state-of-the-art generative models and foundational ML methods to accelerate drug design. This internship focuses on Reinforcement Learning from Human Feedback (RLHF) for molecular generation, adapting techniques that revolutionized large language models to align molecular design models with chemist expertise. See our Google Scholar page for recent publications. Intern candidates should have a strong interest in generative modeling, reinforcement learning, preference learning, and novel mechanisms for guided and controllable generation. The ideal intern is comfortable conducting independent research, rapidly prototyping ideas, and collaborating with multidisciplinary scientists. This internship position is located in South San Francisco, CA, on site.

Requirements

• Current Ph.D. student in Computer Science, Engineering, Statistics, Applied Mathematics, Computational Biology, Computational Chemistry, Physics, or related technical field.
• Strong publication record or evidence of impactful research contributions (e.g., NeurIPS, ICML, ICLR, AISTATS, TMLR, CVPR, ICCV/ECCV)
• Proficiency in Python and modern ML frameworks (PyTorch, TensorFlow, JAX)
• Experience in at least one of the following areas: Reinforcement learning or preference learning Generative modeling (e.g., diffusion models, autoregressive models) Graph neural networks or molecular representation learning

Nice To Haves

• Experience with RLHF methods (e.g., DPO, PPO-RLHF, reward modeling)
• Familiarity with molecular modeling, cheminformatics, or drug discovery applications
• Contributions to open-source ML frameworks or reproducible research environments
• Excellent communication, collaboration, and interdisciplinary working skills

Responsibilities

• Participate in cutting-edge research in ML, 3D generative models, and applications to drug discovery
• Collaborate with cross-functional teams to deliver an impactful, business-critical project
• Develop well-documented code to facilitate adoption of the method
• Present results in the form of a publication, for submission to internal and external scientific conferences

Benefits

• Intensive 12-week, full-time (40 hours per week) paid internship
• Program start dates are in May/June (Summer)
• A stipend, based on location, will be provided to help alleviate costs associated with the internship
• paid holiday time off benefits

What This Job Offers

• Job Type: Full-time
• Career Level: Intern
• Education Level: Ph.D. or professional degree
• Number of Employees: 5,001-10,000 employees