Senior Scientist, Translational Oncology & Biomarkers

Genentech; South San Francisco (CA); On-site; USD 121,000 - 224,000; Full time

Job summary

Genentech is seeking a Scientist 3 in Translational Medicine, Oncology to lead lab-based translational research in lung and GI cancers. You will design experiments validating hypotheses from non-clinical and clinical data, and collaborate with experts to drive biomarker-driven clinical development.

The role emphasizes mechanistic studies, development of advanced assays, and leveraging emerging single-cell and multi-omic technologies to inform patient stratification and combination strategies.

Qualifications

• Ph.D. in relevant field or BA/BS with extensive experience considered.
• Deep knowledge of cancer biology and immunology.
• Ability to lead hands-on lab-based research and develop assays.
• Experience with multi-omics and translational technologies desirable.
• Excellent communication and collaboration skills.

Responsibilities

• Design and execute experiments to validate biological and therapeutic hypotheses.
• Synthesize and interpret data with cross-functional teams.
• Elucidate mechanisms of action and resistance to guide patient selection.
• Identify and validate novel assays and platforms for testing.
• Establish collaborations to access new technologies and data.

Skills

Cancer biology

Immunology

Translational research

Single-cell & multi-omics

Data interpretation

Education

Ph.D. in Cancer Biology, Cell Biology, Immunology, or related

BA/BS or MS with 6+ years of related experience

Tools

Flow cytometry

2D/3D tumor models

Biomarker assays

In vivo models

Job description

Genentech is seeking a Scientist 3 in Translational Medicine, Oncology to lead lab-based translational research in lung and GI cancers. You will design experiments validating hypotheses from non-clinical and clinical data, and collaborate with experts to drive biomarker-driven clinical development.

The role emphasizes mechanistic studies, development of advanced assays, and leveraging emerging single-cell and multi-omic technologies to inform patient stratification and combination strategies.