Machine Learning Scientist, Frontier Research, AI for Drug Discovery (AIDD)
Genentech
Summary
Within AI for Drug Discovery, the Frontier Research team advances fundamental machine learning and statistics methods, motivated by real-world challenges in drug discovery. In biology and medicine, many important problems cannot yet be addressed with off-the-shelf machine learning approaches—they demand not only novel solutions, but also new paradigms for framing and thinking about the problems themselves. Instead of focusing on incremental improvements, we work on long-horizon ideas that require a creative and broad perspective, developing solutions at a level that can be instantiated for multiple internal and external applications.
Job description
The Opportunity
Within AI for Drug Discovery, the Frontier Research team advances fundamental machine learning and statistics methods, motivated by real-world challenges in drug discovery. In biology and medicine, many important problems cannot yet be addressed with off-the-shelf machine learning approaches—they demand not only novel solutions, but also new paradigms for framing and thinking about the problems themselves. Instead of focusing on incremental improvements, we work on long-horizon ideas that require a creative and broad perspective, developing solutions at a level that can be instantiated for multiple internal and external applications.
In this role, you will:
- Develop new methods and frameworks for uncertainty quantification, statistical inference, and experimental design, motivated by the diverse problem settings that arise when using machine learning to guide decision-making across the drug-discovery pipeline.
- Contribute to and drive research projects that result in conference and/or journal publications and open-source code, and that foster cross-organizational collaborations and applications.
- Engage actively in knowledge dissemination, presenting your work and expertise at internal and external scientific conferences.
- Collaborate closely with our team in South San Francisco, New York, and Basel, Switzerland.
Who You Are
- Must be pursuing, or have completed within the last 12 months, a Ph.D. in Computer Science, Statistics, Applied Mathematics, Physics, Computational Biology, or related technical field, or have demonstrated equivalent research productivity.
- Demonstrated expertise in (any paradigm of) uncertainty quantification for decision-making, e.g., sequential/online statistical inference, experimental design, conformal prediction, reinforcement learning, calibration, game-theoretic statistics, etc.
- Proven publication record and experience contributing to the research community, including at conferences like NeurIPS, ICML, ICLR, AISTATS, UAI, etc., and/or relevant journals.
- Excellent skills in technical writing & communication, as well as collaboration and interpersonal skills.
Preferred
- Experience with developing machine learning and/or statistical methods for biological/clinical data is desired, but not necessary.
- Experience developing open-source packages preferred.
Requirements
- Must be pursuing, or have completed within the last 12 months, a Ph.D. in Computer Science, Statistics, Applied Mathematics, Physics, Computational Biology, or related technical field, or have demonstrated equivalent research productivity
- Demonstrated expertise in uncertainty quantification for decision-making (e.g., sequential/online statistical inference, experimental design, conformal prediction, reinforcement learning, calibration, game-theoretic statistics)
- Proven publication record and experience contributing to the research community, including at conferences like NeurIPS, ICML, ICLR, AISTATS, UAI, and/or relevant journals
- Excellent skills in technical writing & communication, as well as collaboration and interpersonal skills
- Experience with developing machine learning and/or statistical methods for biological/clinical data is desired, but not necessary
- Experience developing open-source packages preferred
Benefits
- Discretionary annual bonus
- Medical, Dental & Vision
Company overview
Genentech, founded in 1976 and now a member of the Roche Group, is widely recognized as the pioneer of the biotechnology industry. The company has been at the forefront of scientific innovation for nearly 50 years, using human genetic information to develop novel medicines for serious and life-threatening diseases. Genentech's transformational discoveries include the first targeted antibody for cancer and the first medicine for primary progressive multiple sclerosis. With over 10,000 employees, the company operates from its South San Francisco headquarters and maintains a strong focus on oncology, immunology, neuroscience, ophthalmology, and infectious diseases. Genentech continues to pursue groundbreaking science while maintaining its startup spirit within the Roche organization, consistently delivering on its promise to improve patients' lives through innovative biopharmaceutical solutions.