2026 Summer Intern

2026 Summer Intern - Computational Biology and Medicine - Perturbation

Department Summary

The Computational Biology and Medicine (CBM) department is a key pillar of the Computational Sciences Center of Excellence (CS-CoE) within Genentech's Research and Early Development (gRED) organization. We are a diverse team of computational biologists and data scientists with deep expertise spanning genomic methodologies, multi-modal data analysis, and therapeutic areas.

In CBM, we bridge the gap between dry-lab and wet-lab. We collaborate closely with disease biologists, experimentalists, and AI/ML researchers to deploy rigorous analytical frameworks that drive decision-making. Our mission is to transform complex biological data into actionable insights that accelerate target discovery and biomarker development.

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. You will have the chance to contribute directly to our early discovery pipeline by developing tools to interpret large-scale genetic screening data. You will:

• Explore and Analyze Perturbation Data: Dive into large-scale genetic perturbation datasets (e.g., Perturb-seq) to understand the landscape of gene function and regulation.

• Benchmark Machine Learning Methods: Rigorously test and evaluate statistical and machine learning approaches, such as matrix factorization and other dimensionality reduction techniques, to identify robust gene expression programs and perturbation modules.

• Innovate Annotation Strategies: Develop and apply computational methods to biologically annotate identified modules, connecting statistical signals to meaningful biological mechanisms.

• Build Scientific Software: Design and implement software tools to database, query, and visualize results, enabling wider access to these insights for the broader research team.

• Collaborate and Present: Engage with cross-functional teams and present your research at internal seminars.

Program Highlights

• 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.

Who You Are

Required Education

• Must be pursuing a PhD (enrolled student).

Required Majors:

• Computer Science, Statistics, Mathematics, Computational Biology, Biostatistics, or a related field.

Required Skills: 

• Proficiency in bioinformatics (programming in R or Python, and HPC).

• Experience developing/applying statistical or computational methods to analyze omics data.

• Experience with scRNA-seq data

Preferred Knowledge, Skills, and Qualifications

• Excellent communication, collaboration, and interpersonal skills.

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

• Experience with dimensionality reduction techniques and/or perturbation data.

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 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.