Chan Zuckerberg Biohub Network
Computational Biologist, Single Cell Immunology at Organismal Scale (Biohub SF)
Chan Zuckerberg Biohub Network, San Francisco, California, United States, 94199
Computational Biologist, Single Cell Immunology at Organismal Scale (Biohub SF)
We are seeking a Computational Biologist with deep expertise in omics, experience with machine learning, and familiarity with spatial biology to join our team. 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. Our vision is to pursue large scientific challenges, enable individual investigators to pursue their riskiest and most innovative ideas, and develop technologies that will lead to actionable diagnostics and effective therapies. The successful candidate 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, and contribute to predictive modeling of infection trajectories across heterogeneous cell populations. Responsibilities include: 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 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. Requirements include a 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, and proficiency in Python and experience with machine learning libraries. Essential qualifications include: 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. Proficiency in Python and experience with machine learning libraries. Experience with reproducible research practices, including version control, pipeline frameworks, and documentation. Experience working with high-performance computing environments. Nice to have qualifications include experience in immunology, virology, or zebrafish models, prior work in complex tissue/organism contexts, familiarity with multi-modal data integration, and familiarity with spatial statistics. Nice to have qualifications include: Experience in immunology, virology, or zebrafish models. Prior work in complex tissue/organism contexts. Familiarity with multi-modal data integration. Familiarity with spatial statistics. Contributions to open-source computational biology tools or datasets. We offer a competitive salary range of $108,000 - $149,000 for Computational Biologist I and $132,000 - $182,000 for Computational Biologist II, as well as a range of benefits including a generous employer match on employee 401(k) contributions, paid time off to volunteer, funding for select family-forming benefits, and relocation support. CZ Biohub SF is an equal opportunity employer and welcomes applications from diverse candidates.
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We are seeking a Computational Biologist with deep expertise in omics, experience with machine learning, and familiarity with spatial biology to join our team. 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. Our vision is to pursue large scientific challenges, enable individual investigators to pursue their riskiest and most innovative ideas, and develop technologies that will lead to actionable diagnostics and effective therapies. The successful candidate 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, and contribute to predictive modeling of infection trajectories across heterogeneous cell populations. Responsibilities include: 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 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. Requirements include a 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, and proficiency in Python and experience with machine learning libraries. Essential qualifications include: 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. Proficiency in Python and experience with machine learning libraries. Experience with reproducible research practices, including version control, pipeline frameworks, and documentation. Experience working with high-performance computing environments. Nice to have qualifications include experience in immunology, virology, or zebrafish models, prior work in complex tissue/organism contexts, familiarity with multi-modal data integration, and familiarity with spatial statistics. Nice to have qualifications include: Experience in immunology, virology, or zebrafish models. Prior work in complex tissue/organism contexts. Familiarity with multi-modal data integration. Familiarity with spatial statistics. Contributions to open-source computational biology tools or datasets. We offer a competitive salary range of $108,000 - $149,000 for Computational Biologist I and $132,000 - $182,000 for Computational Biologist II, as well as a range of benefits including a generous employer match on employee 401(k) contributions, paid time off to volunteer, funding for select family-forming benefits, and relocation support. CZ Biohub SF is an equal opportunity employer and welcomes applications from diverse candidates.
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