The Position 2026 Summer Intern - Statistical Methods for Perturbation Analysis (TRAIL) Department Summary The statistical methods group of the Translational AI Lab (TRAIL) is part of Genentech's Research and Early Development (gRED) organization. We develop analytical methods to extract translational insights from large-scale and focused biological data. Currently, we work in close collaboration with wet lab scientists in the Translational Genomics and Proteomics Center (TGP) to develop joint computational and experimental frameworks to map and understand genetic and chemical perturbations at scale. This internship position is located in South San Francisco, on-site. The Opportunity
- Explore large-scale chemical and genetic perturbation data across disease subtypes.
- Test and benchmark existing statistical and machine learning methods.
- Develop and apply novel algorithms to understand context-specific drug mechanisms of action.
- Develop scientific software tools and contribute to manuscripts.
- Collaborate with technology teams to design follow-up experiments.
- Intensive 12-weeks, 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.
- Ownership of challenging and impactful business-critical projects.
- Work with some of the most talented people in the biotechnology industry.
- Must be pursuing a PhD (enrolled student).
- Computer Science, Statistics, Mathematics, Computational Biology, Biostatistics, or a related field.
- Proficiency in bioinformatics (programming and HPC).
- Experience developing statistical or computational methods to analyze omics data.
- Experience with perturbation data is a plus.
- Proactive, resourceful, tenacious.
- Excellent communication, collaboration, and interpersonal skills.
- Complements our culture and the standards that guide our daily behavior & decisions: Integrity, Courage, and Passion.