Genentech Internship | Pay Upto $50/hour | Apply Now !

Genentech is hiring interns for the Statistical Methods – Translational AI Lab internship for Summer 2026 in South San Francisco, California . Explore every key detail below and learn how to apply effectively!

About Genentech

Genentech, a member of the Roche Group, is one of the most respected biotechnology companies in the world. Known for pioneering breakthroughs in cancer research, immunology, and molecular biology, the company blends advanced science with innovative technology to solve complex medical challenges.

What makes Genentech stand out is its strong research culture—scientists, engineers, and data experts collaborate every day to discover therapies that change patient lives. Genentech encourages curiosity, independent thinking, and meaningful scientific exploration, making it a dream destination for students looking to work at the intersection of biology, computation, and medicine.

Internship Overview

📌 Position: Summer Intern – Statistical Methods, Translational AI Lab
📍 Location: South San Francisco, California
🗓 Duration: Summer 2026 internship
⏱ Time Commitment: Full-time

This internship places you in the Translational AI Lab (TRAIL), a group within Genentech’s Research & Early Development (gRED) division. As part of the Statistical Methods team, you will work directly with scientists building computational models to understand disease biology and drug mechanisms.

Unique Insight:

This internship is one of the few opportunities where PhD students can work with real perturbation datasets—genetic, chemical, multi-omics—and contribute algorithms that influence early-stage drug discovery. The exposure to translational data, HPC systems, and experimental collaboration helps students build rare skills that top pharma and biotech companies value.

Roles & Responsibilities

As a Statistical Methods Intern, you will work on high-impact computational research. Key responsibilities include:

Exploring and analyzing large-scale chemical & genetic perturbation datasets across disease models
Evaluating, testing, and benchmarking statistical & machine learning methods
Developing novel algorithms to study drug mechanism of action
Building scientific software tools and contributing to research manuscripts
Collaborating with wet-lab teams to design experimental follow-ups
Presenting weekly progress reports and discussing findings with stakeholders
Supporting computational research pipelines within TRAIL

Unique Value:

You’re not just analyzing data—you’re helping shape real research used by scientists to understand diseases at a molecular level. The models you create can guide experimental decisions, making your work a direct part of Genentech’s discovery pipeline.

Qualifications & Eligibility

Genentech is looking for candidates who meet the following:

Must be currently enrolled in a PhD program
Majors accepted: Computer Science, Statistics, Mathematics, Biostatistics, Computational Biology, or related fields
Strong programming background, especially in bioinformatics + HPC environments
Experience building statistical or computational methods for analyzing omics data
Experience with perturbation datasets is a major plus
Excellent problem-solving, communication, and collaboration skills
Must work onsite in South San Francisco
Authorized to work in the U.S. (the company does not provide relocation benefits for this internship)