2025 Summer Intern - Foundational ML and AI, Regev Lab

Department Summary

Genentech, a leader in biotechnology, is seeking an outstanding machine learning intern to contribute to cutting-edge research at Aviv Regev's lab. Among other priorities, the lab is dedicated to advancing machine learning research to support drug and target discovery efforts. We are committed to driving innovation through cutting-edge ML methods with real-world impact in the target and drug discovery field.

This position is based in South San Francisco, On Site.

The Opportunity

Join us for a 12-week summer internship (full-time, 40 hours per week) from May/June 2025 at our South San Francisco location (on-site), providing you with an exciting opportunity to work alongside our collaborative research team of machine learning scientists, computational biologists, and chemists, and make a substantial contribution to the field. The candidate will collaborate in an interdisciplinary team including colleagues from within the Regev lab, computational biology teams and artificial intelligence/machine learning departments.

Responsibilities

• Research, design, and implement novel, cutting-edge research in ML with applications to single-cell RNAseq.

• Drive research on foundational AI methods for scientific problems, with a specific focus on foundation models and representation learning.

• Collaborate closely with cross-functional teams across Genentech to tackle complex biological problems.

• Contribute to and lead publications, presenting results at internal and external scientific conferences, and making code and workflows open source.

Who You Are

Required Education

Must be pursuing a PhD (enrolled student), where your core focus is on machine learning, artificial intelligence, statistics, computational biology, or related fields.

Required Majors

Computational Biology or AI/ML learning.

Required Skills

• Strong publication record at top-tier ML venues such as NeurIPS, ICML, ICLR, AISTATS, or equivalent.

• Strong theoretical foundations of representation learning and generative models.

• Excellent programming skills in PyTorch.

• Strong communication and collaboration skills.

Preferred Qualifications

• Hands-on experience in designing, training, extending, or applying foundation models and large-scale models for single-cell RNAseq data.

• Experience in developing and applying representation learning methods (e.g., generative, contrastive, graph-based, etc.).

• Familiarity with biological problems such as single-cell biology, sequence design, perturbation biology, and/or target discovery, and related data types.

Relocation benefits are not available for this job posting.

The expected salary for this position based on the primary location 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, and we embrace the increasingly diverse world around us. Genentech prohibits unlawful discrimination based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin or ancestry, age, disability, marital status and veteran status.