Computational Biologist / Bioinformatics Scientist (IBD) (Contract)

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Position Overview

We are seeking a passionate and creative scientist to join the Computational Sciences Center of Excellence (CS CoE) within Genentech Research and Early Development (gRED). The successful candidate will work in a highly collaborative, interdisciplinary environment, interfacing with both biomarker scientists and experimental biologists to drive drug discovery and development.

Scope of Work

The candidate will be responsible for the development and application of a computational framework for the integration and analysis of clinical molecular data as well as biological interpretation of results to support informed decision-making throughout the IBD research and development processes. This computational framework consists of a suite of interoperable AI/ML enabled analysis pipelines that leverages single cell, spatial transcriptomics, proteomics and histology data. The specific tasks include:

1. Development and application of an IBD clinical atlas to address critical R&D questions.This task involves leveraging integrated clinical and molecular data from multiple trials across various mechanisms of action (MoAs) into a unified atlas. Core responsibilities encompass data preparation including curation and quality control, followed by robust analysis and biological interpretation to drive high-priority research use cases, such as patient endotyping, discovering generalized molecular biomarkers, and modeling advanced patient outcomes. Furthermore, the candidate will provide operational coordination and scientific or strategic expertise to effectively integrate these data-driven insights with broader research and development goals.
2. Establishment of a scalable infrastructure and standardized feature reference for foundational AI models.This task focuses on scaling computational approaches for single-cell and spatial datasets to support broader organizational AI initiatives and dedicated agentic systems. A primary responsibility will be establishing and maintaining an expert-informed feature catalog that captures key molecular and clinical disease characteristics, such as cell states, transcriptional programs, pathological niches, and patient cohorts. This structured reference will serve as a standardized analytical foundation to train the next generation of multipurpose AI models, enrich organizational knowledge graphs, and enhance exploratory data analyses.

Expertise & Experience

• The ideal candidate will possess a strong background in immunology and computational biology, with in-depth knowledge of IBD pathogenesis, relevant immune pathways, and current therapeutic landscape. Furthermore, they should have demonstrated experience in applying AI/ML methods to analyze complex biological datasets, particularly multimodal omics and clinical data.
• Excellent communication and collaboration skills are required to effectively interact with AI scientists, computational biologists, experimental scientists, and clinicians, including the ability to present complex computational findings, assess their limitations and formulate follow-up hypotheses.
• Preferred: Prior experience in the analysis of immune-mediated inflammatory diseases (IMID).
• Education: B.S., Master’s or PhD in Computational Biology, Systems Biology, Bioinformatics, Genomics, Immunology, Statistics, or a related quantitative field.

Technical Skills

• Programming: Expert-level proficiency in R and/or Python.
• Statistics: Deep understanding of statistical frameworks for genomic data, such as batch effect detection, covariate adjustment, NMF, Manifold Learning, or Factor Analysis.
• Single-cell analysis: Proven hands-on experience in single-cell and/or spatial immune profiling.
• Computational Environment: Proficiency using Linux-based servers, high-performance computing (HPC), agentic coding, and version control systems like Git.

Engagement Details

• Location: On-site in South San Francisco, CA.
• Schedule: Full-time (40 hours/week).

Application Questions

1. Have you analyzed single-cell or spatial-transcriptomics data to study a research question in immunology? Has it been published? Will you be able to present the study?
2. Do you have experience with integration of large clinical datasets? What tools did you use? What technical challenges did you overcome?
3. What field in human immunology are you interested in? (e.g. cell-types, pathways, diseases)

Start and Commitment

• Start date: ASAP
• Commitment: Full-time 100%. 1 year to start.

How to Apply

This contract role was shared by the hiring contact in a LinkedIn post, with the job description attached (reference CBM_27_32). To apply, send your resume and your answers to the application questions above to the poster through the LinkedIn post.