Roche-posted 10 days ago
Full-time • Intern
Onsite • South San Francisco, CA
5,001-10,000 employees

We are now accepting applications for the Genentech 2026 Summer Internship Program in Development Sciences (DevSci); this post is for a computational biology role in Translational Safety (TS). Translational Safety is an integral part of DevSci. We contribute to the organization’s success by providing scientific insights and ensuring the safety of molecules that advance through the pipeline to patients. We do this to support the DevSci vision to deliver the right drug in the right dose to the right patient. We are also committed to providing better outcomes for our people, patients, business, and communities by advancing and boldly championing diversity, equity, and inclusion in our work. The selected candidate will integrate single-cell RNA-seq and ATAC-seq data to evaluate how well in vitro liver models reproduce in vivo toxicant responses. Using AI-based modeling, the intern will determine whether cell-specific chromatin accessibility changes can predict transcriptional activation patterns. These insights will define the translational utility of in vitro systems and inform the design of more predictive, human-relevant liver toxicity models. This internship position is located in South San Francisco, on-site.

  • Integrate Multiomic Data: Process and analyze single-cell RNA-seq and scATAC-seq datasets to map regulatory landscapes.
  • Benchmark Model Performance: Compare in vitro liver model responses against in vivo profiles to evaluate how accurately lab models reproduce toxicant-induced cellular programs and injury pathways.
  • Develop AI Predictive Models: Build and test AI/machine learning frameworks to determine if chromatin accessibility changes can accurately predict downstream transcriptional activation and gene expression.
  • Drive Translational Impact: Generate mechanistic insights that define the utility of current experimental systems.
  • Required Education: Must be currently pursuing a PhD (enrolled student).
  • Required Majors/Coursework: STEM Major (preferably in Toxicology or related) with coursework in Bioinformatics, Computational Biology, Data Science, Computer Science, Information Technology, Bioengineering or similar.
  • Required Skills: Proficient in coding with R or Python.
  • Experience working in an HPC/cloud environment to manage large biological datasets.
  • Familiarity with machine learning frameworks or predictive modeling, specifically applied to biological data.
  • Previous experience working with single-cell/ATACseq data is highly desirable.
  • Excellent communication, collaboration, and interpersonal skills.
  • Complements our culture and the standards that guide our daily behavior & decisions: Integrity, Courage, and Passion.
  • Knowledge of liver biology and toxicology.
  • Experience reading scientific journals.
  • Intensive 12-weeks, full-time (40 hours per week) paid internship.
  • Program start dates are in May/June 2026.
  • 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.
  • paid holiday time off benefits
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