2026 Summer Intern - Computational biology and medicine - Neuroscience
About The Position
A healthier future. It’s what drives us to innovate. To continuously advance science and ensure everyone has access to the healthcare they need today and for generations to come. Creating a world where we all have more time with the people we love. That’s what makes us Roche. Advances in AI, data, and computational sciences are transforming drug discovery and development. Roche’s Research and Early Development organisations at Genentech (gRED) and Pharma (pRED) have demonstrated how these technologies accelerate R&D, leveraging data and novel computational models to drive impact. Seamless data sharing and access to models across gRED and pRED are essential to maximising these opportunities. The new computational sciences Center of Excellence (CoE) is a strategic, unified group whose goal is to harness this transformative power of data and Artificial Intelligence (AI) to assist our scientists in both pRED and gRED to deliver more innovative and transformative medicines for patients worldwide. This internship position is located in South San Francisco, On - Site. The Opportunity As a computational biology intern, you will join a vibrant, rigorous, and industry-leading research community. The goal of this internship is to build a comprehensive single-cell atlas of human iPSC-derived cells to improve experimental decision-making and disease modeling.
Requirements
- Must be currently pursuing a PhD (enrolled student).
- Bioinformatics, Neuroscience, Computational Biology, Statistics, or a related field.
- Proficiency in R or Python for large-scale single-cell transcriptomic analysis.
- Hands-on experience with computational biology workflows and data integration techniques.
- Familiarity with neurobiology.
Nice To Haves
- Experience or strong interest in developing interactive data visualization tools (e.g., R Shiny).
- Experience working with iPSC-derived cellular models.
- Knowledge of benchmarking strategies for data integration.
Responsibilities
- Data Integration: Harmonize and process diverse single-cell RNA-seq (scRNA-seq) datasets from internal and public sources, including multiple protocols and iPSC lines.
- Benchmarking & Analysis: Evaluate and apply various dimensionality reduction and alignment methods to create a unified embedding space.
- Cellular State Characterization: Identify and characterize transcriptomic diversity in under baseline and stimulated conditions.
- App Development: Build and deploy an interactive application to enable researchers to query embedding spaces and visualize gene expression patterns across different model systems.
- Collaborate and present: Engage with cross-functional teams in Roche/Genentech and present your research at internal seminars
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What This Job Offers
Job Type
Full-time
Career Level
Intern
Education Level
Ph.D. or professional degree
