We are looking for a postdoctoral fellow to join the AI for Drug Discovery department of the Genentech Computational Sciences Center of Excellence (CS CoE). The position focuses on developing scalable methods for sequential experimental design in modern machine learning systems, with applications to hyperparameter optimization, model selection, and compute-aware adaptation.
Requirements
- Ph.D. in computer science, statistics, physics, or related computational field
- Strong publication record and experience contributing to research communities, including journals and conferences in machine learning or statistics
- Demonstrated expertise in one or more relevant areas, such as Bayesian optimization, active learning, reinforcement learning, bandits, adaptive experimentation, control, and online optimization
- Independent, motivated, and highly collaborative, with interests in both the theory and practice of adaptive experimentation
Benefits
- Relocation benefits available
- Competitive salary and fully funded research expenses
- Access to world-class seminars, professional development workshops, and networking opportunities
- Health insurance
- Retirement plan