Computational Biologist, Single Cell Immunology at Organismal Scale (Biohub SF)

The Team

The Chan Zuckerberg Biohub San Francisco (CZ Biohub SF) (https://www.czbiohub.org/sf/) is an independent nonprofit research institute that brings together three powerhouse universities - Stanford, UC Berkeley, and UC San Francisco - into a single collaborative technology and discovery engine. CZ Biohub SF itself supports some of the brightest, boldest engineers, data scientists, and biomedical researchers to investigate the fundamental mechanisms underlying disease and develop new technologies that will lead to actionable diagnostics and effective therapies. We are guided by our values of scholarly excellence; disruptive innovation; hands-on engineering/hacking/building; partnership and collaboration; open communication and respect; inclusiveness; and opportunity for all.

Our Vision

• We pursue large scientific challenges that cannot be pursued in conventional environments
• We enable individual investigators to pursue their riskiest and most innovative ideas
• The technologies developed at CZ Biohub San Francisco facilitate research by scientists and clinicians at our home institutions and beyond

Diversity of thought, ideas, and perspectives are at the heart of CZ Biohub Network and enable disruptive innovation and scholarly excellence. We are committed to cultivating an organization where all colleagues feel inspired and know their work makes an important contribution.

The Opportunity

We’re a cross-disciplinary institute on a mission to illuminate the entire immune system with unparalleled scope and resolution. Our approach is to make holistic measurements of immune cell types, states, and interactions through dynamic profiling of the system in health and disease states. We use cutting edge molecular profiling and imaging coupled with statistics and AI/ML to decode the inputs and outputs of the immune system during virus infection and other inflammatory contexts. The Balla Lab is pioneering this effort in zebrafish, enabling dynamic and spatially resolved analyses of the entire immune system at single cell resolution.

To advance this initiative, we’re hiring a Computational Biologist with deep expertise in omics, experience with machine learning, and familiarity with spatial biology. We’re looking for someone who can operate with a high level of independence, guide technical strategy, and contribute leadership in both collaborative planning and data-driven discovery. You’ll take charge of developing and refining computational pipelines and models that integrate multiple modalities of data, leading efforts to uncover interpretable patterns of immune responses to virus infection and other inflammatory perturbations. Your work will uncover novel insights into the organizing principles and dynamics of the immune system at unprecedented scale and resolution.

This role will be based in San Francisco initially with a planned transition to Redwood City in two years.

What You'll Do

• Design, implement, and maintain robust pipelines for omics data processing, integration, and visualization.
• Develop and apply machine learning models to identify signatures of health and disease states.
• Contribute to predictive modeling of infection trajectories across heterogeneous cell populations.
• Take initiative in shaping the computational direction of the project and collaborate with molecular biologists, immunologists, and virologists to plan experiments and interpret findings.
• Share your expertise with team members, mentor junior staff, and help define best practices for data analysis and infrastructure.
• Author high-impact publications and present findings at internal meetings and international conferences.
• Document and release code and datasets for open-source use, ensuring long-term reproducibility and accessibility.

What You'll Bring

Essential –

• PhD. or equivalent experience in Computational Biology, Bioinformatics, Systems Biology, or a related discipline.
• 3 years of post-PhD experience performing integrated data analysis using single cell omics assays, including demonstrated leadership or independent contributions to complex computational biology projects.
• Proficiency in Python (or similar languages) and experience with machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch).
• Experience with reproducible research practices, including version control, pipeline frameworks (e.g., Snakemake, Nextflow), and documentation.
• Experience working with high-performance computing environments.

Nice to have -

• Experience in immunology, virology, or zebrafish models.
• Prior work in complex tissue/organism contexts.
• Familiarity with multi-modal data integration (e.g., imaging, ATAC-seq, spatial transcriptomics).
• Familiarity with spatial statistics.
• Contributions to open-source computational biology tools or datasets.

Compensation

The San Francisco, CA base pay range for a new hire in this role is Computational Biologist I = $108,000.00 - $149,000.00 and Computational Biologist II = $132,000.00 - $182,000.00. New hires are typically hired into the lower portion of the range, enabling employee growth in the range over time. Actual placement in range is based on job-related skills and experience, as evaluated throughout the interview process. 

Benefits for the Whole You 

We’re thankful to have an incredible team behind our work. To honor their commitment, we offer a wide range of benefits to support the people who make all we do possible. 

• Provides a generous employer match on employee 401(k) contributions to support planning for the future.
• Paid time off to volunteer at an organization of your choice. 
• Funding for select family-forming benefits. 
• Relocation support for employees who need assistance moving

If you’re interested in a role but your previous experience doesn’t perfectly align with each qualification in the job description, we still encourage you to apply as you may be the perfect fit for this or another role.

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