2026 Fall Intern - Translational Medicine Oncology

Genentech • South San Francisco, CA • 3h ago

The Position

Department Summary

We are looking for a skilled and enthusiastic intern to join our vibrant team in Translational Medicine Oncology at Genentech's Research & Development division (gRED). The chosen candidate will immerse themselves in a cross-functional environment that bridges Translational Medicine, Computational Sciences Biology, Technology Innovation and Clinical Sciences. Their focus will be on investigating drug mechanisms of action and resistance in colon cancer through the analysis and interpretation of mouse and human genomic data from implanted tumors in mice and matched primary and metastatic tumors from humans.

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

The Opportunity

Drive a scientific and analytical translational research project in the field of targeted therapy for colon cancer, mentored by a community of scientific experts in oncology, computational biology, and translational research.

Dive into clinical and transcriptomics/genomics data from both mouse studies and clinical trial patients to investigate tumor biology, accelerating translational research with the potential to discover novel biomarkers predictive of response and/or resistance to treatment.

Gain visibility into late-stage, global drug development programs that incorporate a personalized healthcare strategy.

Interact with key cross-functional groups including Clinical Sciences, gRED Computational Sciences (gCS), Operational Diagnostics Technology (ODT) team, and Biostatics team.

Program Highlights

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

Program start dates are in September (Fall).

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)

Required Education

You meet one of the following criteria:

Must be pursuing a Master's Degree (enrolled student).

Must be pursuing a PhD (enrolled student).

Required Majors: Bioinformatics, Computational Biology, Molecular Biology, or related field.

Required Skills:

Competent in computational data analysis programs (i.e. R, Python).

Possess strong analytical and critical thinking skills, able to work cross functionally and collaborate with key stakeholders.

Have a basic understanding of cancer biology and/or related molecular mechanisms in biology.

Effective in conveying information with attention to detail and the ability to present to varied audiences.

Preferred Knowledge, Skills, and Qualifications:

Excellent communication, collaboration, and interpersonal skills.

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

Experience in transcriptomics or genomics data analysis.

Relocation benefits are not available for this job posting.

The expected salary range for this position based on the primary location of California is $40.00-$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 (https://docs.google.com/forms/d/e/1FAIpQLSdZWlsbfQOvFVIQgHE_iDzWUTlhZvj6FytIzjS7xq6IGh1H5g/viewform) .

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