2026 Machine Learning Scientist Summer Intern - Biology Research | AI Development
About The Position
This internship position is located in South San Francisco, On Site. Department Summary At Genentech Research & Early Development (gRED) we have initiated an exciting journey to bring together and further strengthen our computational talent and capabilities by forming a new, central organization - gRED Computational Sciences Center of Excellence (CS CoE). CS CoE is on a mission to partner across the organization to realize the potential of data, technology and computational approaches that will revolutionize how targets and therapeutics are discovered and developed, ultimately enabling novel treatments for patients across the world. We stand at the beginning of this exciting journey. BRAID (Biology Research | AI Development) is a department within CS CoE that focuses on developing and applying machine learning methods to impact biological discovery, with the ultimate goal of impacting drug discovery and human health. We collaborate with clinical scientists, biologists, and engineers to advance the drug development pipelines across disease areas. We are searching for a motivated summer intern to work on designing, developing, and interpreting foundation models for biological data. You will join an established team of AI scientists with a common goal of developing our next generation multi-scale foundation models using cutting-edge AI techniques from graph learning and generative modeling. You will develop models and interpretability methods that identify multi-cellular interactions relevant to patient phenotypes that inform trial design, biomarker selection, and target discovery. This internship position is located in South San Francisco, On-Site. The Opportunity You will lead the development of explainable models and interpretation methods for identifying multivariable features of interest. To benchmark the approach, publicly available datasets with existing supervision can be used for performance evaluation. There will be opportunities to apply the method on novel data collected in the lab, targeting dedicated biological questions. You will produce weekly reports of their progress and compile their findings in a final project report that could be used as a basis for a machine learning conference paper submission. The intern will continuously suggest new experiments and modeling strategies based on previous results. Program Highlights Full time 12 weeks (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. Opportunity to shape the research agenda of the project
Requirements
- Must be pursuing a PhD (enrolled student). in CS, Computational Biology, Engineering, Stats, or related field.
- Computer Science, Computational Biology, Statistics, Engineering, or relevant technical experience.
- Experience with large scale deep learning training infrastructure.
- Experience with model explainability methods (e.g. SHAP, Integrated Gradients).
- Excellent academic presentation and writing skills
Nice To Haves
- Experience with scRNA-seq and genomics data
Responsibilities
- Lead the development of explainable models and interpretation methods for identifying multivariable features of interest.
- Benchmark the approach, publicly available datasets with existing supervision can be used for performance evaluation.
- Apply the method on novel data collected in the lab, targeting dedicated biological questions.
- Produce weekly reports of their progress and compile their findings in a final project report that could be used as a basis for a machine learning conference paper submission.
- Continuously suggest new experiments and modeling strategies based on previous results.
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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
