2025 Fall Intern - Biological Research - AI Development

Department Summary
BRAID is a department within Genentech dedicated to advancing biological and clinical sciences through artificial intelligence. Our core focus is on developing foundation models-general-purpose AI models trained on large-scale biological datasets-which we fine-tune for specialized applications. Our research spans multiple areas, with key focuses including:
High-throughput perturbative screening for target identification and drug discovery, utilizing technologies such as cell painting, Perturb-seq, and optical pooled screens.
Regulatory element design for gene and cell therapy applications.
Integration of multi-modal biological data to improve target assessment.
Inference of cellular communication using spatial transcriptomics and proteomics.
Virtual screening of small molecules for phenotypic drug discovery.
Foundational machine learning, focusing on fine-tuning foundation models, generative modeling, causal inference, explainability, and uncertainty quantification.

This internship position is located in South San Francisco, on-site.

The Opportunity
Perturb-Seq enables the generation of genome-wide Perturbation Atlases which have the potential to improve our understanding of disease mechanisms via identification and characterization of gene regulatory network modules. As more atlases become available, scalable and interpretable computational methods for identifying the shared gene regulatory networks from these atlases are lacking, which limits the insights about disease biology that we can derive from these data.

Tensor factorization (TF) methods are promising approaches for detecting shared gene regulatory programs across millions of single cells from one genome-wide perturbation atlas or across multiple genome-wide perturbation atlases. However, existing TF methods are not yet optimized for analysis of atlas level datasets and not able to leverage user-provided biologically relevant knowledge.

The Li Lab and Melo Carlos Labs are looking for an exceptional intern candidate to work on developing a novel TF method that addresses the described computational challenges. The candidate will have opportunities to learn and implement state-of-the-art tensor decomposition algorithms and apply them to real world genome-scale Perturb-Seq atlas data generated internally at Genentech.

The candidate will work with lab members from Li Lab and Melo Carlos Lab - Dr. Li will supervise the method development and co-mentor Dr. Melo Carlos will provide feedback on evaluating the developed methods on real data.

Program Highlights

• Intensive 12-weeks, full-time (40 hours per week) paid internship, with the option of extending another 4 weeks.

• Program start dates are in September(Fall).

• 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 Sciences/Computational Biology/Bioinformatics

Required Skills:

• Strong background in computer science, statistics or mathematics

• Proficient in Python programming language and its data science environment (e.g. Numpy, Scipy, Pandas, Scikit-learn)

• Experience in single-cell genomics data analysis

Preferred Knowledge, Skills, and Qualifications

• Experience in dimensionality reduction and/or tensor decomposition methods such as non-negative matrix factorization or PARAFAC2 is a plus

• Experience using relevant tools such as JAX and TensorLy is a plus

• 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 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.

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