The Position

2026 Summer Intern - CS-CoE (Computational Biology & Single-Cell/Spatial Proteomics)

Department Summary

Our group develops computational methods that turn high-dimensional data into actionable biological insight. We work at the intersection of machine learning, statistical modeling, and experimental biology, with a focus on robust and reproducible analytics for modern single-cell modalities. This internship will contribute to methods development for network inference using emerging single-cell and spatial proteomics data, with the goal of producing a publication-quality methods study and an internally reusable analysis pipeline.

This internship position is located in South San Francisco, California On Site.

The Opportunity

• Develop FAVA-X, a cross-modality extension of the FAVA network-inference framework, enabling functional network inference from single-cell and/or spatial proteomics while accounting for modality-specific noise characteristics and missingness.

• Evaluate VAE-based (and alternative) representation learning approaches to stabilize inferred networks, improve robustness across subsamples, and enable uncertainty quantification of network edges.

• Design and implement a multimodal network integration strategy (e.g., RNA + protein; single-cell + spatial) and systematically assess whether integration improves edge stability, biological coherence, and interpretability.

• Build a reproducible benchmarking pipeline using public datasets and standardized evaluation metrics, including reproducibility across data splits, pathway and functional coherence, cell-type specificity, and predictive or held-out validation.

• Communicate results through a publication-ready methods report, figures suitable for a manuscript or preprint, and a well-documented, reusable codebase (notebooks and/or packaged pipeline).

Program Highlights

• Intensive 12-weeks, full-time (40 hours per week) paid internship.

• Program start dates are in May/June (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 have attained a Master's Degree.

• Must be pursuing a PhD (enrolled student).

Required Majors

Computational Biology, Bioinformatics, Data Science, Statistics, Computer Science, Biomedical Engineering, Systems Biology (or related quantitative field).

Required Skills

• Strong Python skills for data analysis (NumPy/Pandas/scverse-ecosystem).

• Foundations in statistics and/or machine learning (regression, probabilistic modeling, evaluation).

• Experience working with high-dimensional biological data (single-cell preferred).

• Ability to write clean, reproducible code (version control, documentation, notebooks/pipelines).

Preferred Knowledge, Skills, and Qualifications

• Familiarity with representation learning / deep learning (e.g., VAEs; PyTorch/JAX).

• Experience with proteomics and/or spatial omics data analysis.

• Experience with benchmarking and metrics design; comfort with HPC/cluster environments.

• Excellent communication, collaboration, and interpersonal skills.

• Complements our culture and the standards that guide our daily behavior & decisions: Integrity, Courage, and Passion.

• Any other skills (preferred but not required to have)

Relocation benefits are not available for this job posting. 

The expected salary range for this position based on the primary location of the state of California is $50.00 per 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.

If you have a disability and need an accommodation in relation to the online application process, please contact us by completing this form Accommodations for Applicants.