Scientist 3 – Translational Medicine – OMNI – Inflammatory Bowel Disease

The Position

Genentech's Translational Medicine OMNI (TM OMNI) Department supports the entire R&D portfolio of novel therapies in Ophthalmology, Metabolism, Neuroscience, Immunology, and Infectious Diseases (OMNI). We develop and implement biomarker strategies to study disease pathways, confirm a therapeutic's mechanism of action, and improve clinical trial efficiency and success. Additionally, we conduct foundational clinical translational research to study the molecular and cellular pathways driving disease to generate novel target and biomarker approaches.

Within Inflammatory Bowel Disease (IBD), we focus on integrating clinical and translational research to understand disease heterogeneity, mucosal immune dysregulation, and mechanisms of tissue damage and repair. We leverage clinical trial data, human biospecimens, and high-dimensional omics technologies to drive biomarker discovery and patient stratification, and enable reverse translation to accelerate therapeutic development.

The Opportunity

As a Scientist 3 in Translational Medicine OMNI, you will play a pivotal role in advancing our research in Inflammatory Bowel Disease (IBD). Positioned at the intersection of wet-lab experimentation and data science, you will collaborate with interdisciplinary teams to identify and validate novel therapeutic targets and biomarkers. In this high-impact role, you will apply human-relevant models and high-dimensional omics data to drive biomarker discovery and enable reverse translation, directly influencing clinical development strategies.

• Design and perform experimental studies using patient-derived human biospecimens (e.g., intestinal tissue biopsies, blood, stool) to unravel disease mechanisms in IBD.

• Establish and execute complex human-relevant model systems (including intestinal organoids, primary immune cell co-cultures, and air-liquid interface systems) to investigate pathway biology and therapeutic mechanisms of action.

• Develop, qualify, and execute custom assays (e.g., multiplex immunoassays, ELISA, flow cytometry, histology) to generate pharmacodynamic and disease-relevant readouts.

• Analyze and integrate high-dimensional datasets (scRNA-seq, CITE-seq, spatial transcriptomics, proteomics) using R or Python to discover biomarkers and support patient stratification.

• Support clinical biomarker research strategies by translating laboratory findings into actionable insights for cross-functional clinical development programs.

• Evaluate and implement emerging technologies and experimental platforms to continually advance our translational research capabilities in IBD.

• Collaborate closely with cross-functional partners across Research, Bioanalytical Sciences, Biostatistics, Computational Sciences, and Clinical Development to present findings and drive project goals.

Who you are

• Education: PhD with post-doctoral experience in Immunology, Cell/Molecular Biology, Mucosal Biology, Biochemistry, or a related life sciences discipline, backed by a strong peer-reviewed publication record.

• Experience: Minimum of 3 years of hands-on experience in immunology or mucosal biology, ideally focused on Inflammatory Bowel Disease (IBD) research.

• Technical Expert: Proven technical expertise in benchtop techniques (flow cytometry, multiplex immunoassays, ELISA, RT-qPCR, histology) and single-cell workflows (scRNA-seq, CITE-seq).

• Analytical: Proficient in coding with R or Python for analyzing, visualizing, and interpreting large-scale preclinical and clinical omics datasets.

• Independent Scientist: Demonstrated ability to independently design, execute, and troubleshoot complex scientific studies while managing multiple priorities in a collaborative environment.

Preferred

• Direct hands-on experience with primary cell isolation from human intestinal tissue.

• Advanced expertise with complex disease models, including 3D organoid cultures, co-culture systems, air-liquid interface organoids, or microphysiological systems (gut-on-a-chip).

• Experience using computational tools to directly analyze high-dimensional single-cell, spatial transcriptomics, or proteomics data beyond standard bench generation.

• Demonstrated track record of effective cross-functional collaboration within a matrixed, interdisciplinary research environment.

• Willingness to work in an open, highly collaborative environment with flexibility for global busin