Computational Biologist, Single Cell Immunology at Organismal Scale; Biohub SF

The Chan Zuckerberg Biohub San Francisco (CZ Biohub 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.
  
  You will
  
  - 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.
  
  You have
  
  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…