Job Description

2025 Fall Intern - gRED, Regev Lab

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

The Opportunity

• Apply sequence-to-function (S2F) models (e.g., Decima, Borzoi) to predict regulatory variant effects across cell types and states.

• Incorporate predictions as mechanistic priors in fine-mapping methods like Susie for improved causal variant identification.

• Prioritize relevant cell types, transcription factors, and regulatory pathways using learned parameters.

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• Evaluate methods on generalization (across ancestries) and polygenic risk score accuracy.

Program Highlights

• Full time for at least the first 12 weeks (40 hours per week) paid internship.

• Program start dates are in September/October (Autumn)

• 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

Enrolled PhD student or a recent graduate in a relevant field.

Required Majors

Statistical Genetics & Computational Sciences

Required Skills

• Experience with data driven method development. 

• Familiarity with time series data and dynamical process modeling. 

• Knowledge and experience with deep learning frameworks. 

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.