2026 Summer Intern - Computational Cancer Biology & AI

2026 Summer Intern - Computational Cancer Biology & AI

Department Summary

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 organizations 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 is located in South San Francisco, California On-Site.

The Opportunity

This project offers a unique opportunity for a talented intern to work at the intersection of deep learning, genomics, and cancer biology. The intern will apply multi-modal foundation models to novel high-throughput functional genomics datasets to predict how cancer cells respond to genetic perturbations. The core of the project will involve not only predicting these responses but also delving into under hood using model interpretability techniques. Here, the overarching goal is to uncover biologically relevant biomarkers that explain why certain perturbations have profound effects in specific contexts, thereby guiding future target discovery. Over a 3- or 6-month period (6-preferred, but >3- is workable), the intern will gain hands-on experience with large-scale genomic data analysis, and cutting-edge machine learning methods in oncology.

Program Highlights

• Intensive 6-month, full-time (40 hours per week) paid internship.

• Program start dates are in May/June 2025.

• A stipend 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.

Who You Are

Required Education

You must be pursuing a PhD (enrolled student)

Required Majors

Computational Biology, Bioinformatics, Statistics, Computer Science, or related fields.

Required Skills

• Strong proficiency in coding with Python.

• Deep knowledge of traditional machine learning, statistical principles, regression analysis.

• Experience with transformer-based foundation models and/or modern AI frameworks; eg. PyTorch

• Previous experience working with genomic data, especially single-cell data, is highly desirable.

Preferred Knowledge, Skills, and Qualifications

• Good understanding of cancer biology, oncogenic mechanisms & signaling pathways.

• Excellent communication, collaboration, and interpersonal skills.

• Complements our culture and the standards that guide our daily behavior & decisions: Integrity, Courage, and Passion.

Relocation benefits are not available for this job posting.

The expected salary range for this position based on the primary location of the state of California is $50.00 per hour. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. This position also qualifies for paid holiday time off benefits.

Genentech is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company's policy prohibits unlawful discrimination, including but not limited to, discrimination on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws.

If you have a disability and need an accommodation in relation to the online application process, please contact us by completing this form Accommodations for Applicants.