2026 Summer Intern - Computational Biology and Medicine

Description du poste:

2026 Summer Intern - Computational Biology and Medicine

Department Summary

The Center for Excellence for Computational Sciences at Roche/Genentech is a data-driven organization focused on transforming how targets and therapeutics are discovered and developed. Within this division, the Computational Biology and Medicine (CBM) department analyzes biological and clinical data to advance the drug development pipeline. The successful candidate will collaborate with computational biologists in the CBM Neuroscience and Translational Medicine groups to analyze proteomic data from three multiple sclerosis clinical trials and develop an R Shiny application to support data sharing and data-driven decisions across early- and late-stage MS programs.

This internship position is located in SSF or remote (USA only).

The Opportunity
* Build a unified proteomics integration framework that harmonizes data across clinical studies and measurement platforms.
* Build and deploy an interactive R Shiny application that enables cross-study querying, visualization, and exploration of proteomic biomarkers.
* Create standardized data structures to support scalable cross-trial analysis and future expansion of the platform as new clinical datasets become available.
* Develop dynamic visualization modules, including expression patterns, clinical and imaging correlations, treatment-effect summaries, and survival analyses.
* Integrate proteomic insights with internally generated single-cell and single-nucleus RNA-seq atlases to support biological interpretation and target or biomarker discovery.

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 be pursuing a Master's Degree or PhD (enrolled student, PhD preferred).

Required Majors:
Bioinformatics, Computational biology, Statistics, Computer Science

Required Skills:
* Strong proficiency in R and experience building R Shiny applications for data visualization and exploration.
* Demonstrated ability to work with large, multi-modal biological datasets, including data cleaning, harmonization, and structuring for analysis.
* Solid understanding of statistical modeling and common analytical methods (e.g., correlation analysis, survival analysis, treatment-effect estimation).
* Familiarity with proteomics or other high-dimensional omics data types.
* Ability to communicate technical findings clearly and collaborate effectively with cross-functional scientific teams.

Preferred Knowledge, Skills, and Qualifications
* Experience integrating or visualizing single-cell or single-nucleus RNA-seq datasets
* Background in neuroscience, immunology, or related biomedical fields.
* Experience with interactive dashboard design, UX considerations, or front-end visualization libraries.
* 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 New York 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.

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