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2025 Summer Intern - gRED, Regev Lab

Genentech
United States, California, South San Francisco
Jan 18, 2025
The Position 2025 Summer Intern - gRED, Regev Lab

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

The Opportunity

  • Adapt reasoning-expansion techniques, inspired by Quiet-STaR, to enable multimodal LLM to expand reasoning steps before predictions on microscopy images of cells.

  • Enhance the model's ability to integrate world knowledge and implicit reasoning for analyzing complex cellular patterns and biomedical tasks.

  • Improve performance in challenging prediction rounds (e.g., those requiring advanced reasoning and biomedical common sense).

  • Evaluate the approach using metrics reflecting reasoning robustness and accuracy in cellular microscopy image analysis.

Program Highlights

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

  • Program start dates are in May (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 Degree (enrolled student)

Required Majors

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.

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