Chan Zuckerberg Biohub Network
Senior Research Scientist, AI/ML (Biohub SF)
Chan Zuckerberg Biohub Network, San Francisco, California, United States, 94199
Overview
Computational Biologist, Single Cell Immunology at Organismal Scale (Biohub SF) is a post-graduate level research role focused on developing and applying computational methods to multi-modal data in immunology, with emphasis on single-cell omics, spatial biology, and machine learning. The position is based in San Francisco 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 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 - $149,000 and Computational Biologist II = $132,000 - $182,000. 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
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.
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Computational Biologist, Single Cell Immunology at Organismal Scale (Biohub SF) is a post-graduate level research role focused on developing and applying computational methods to multi-modal data in immunology, with emphasis on single-cell omics, spatial biology, and machine learning. The position is based in San Francisco 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 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 - $149,000 and Computational Biologist II = $132,000 - $182,000. 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
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.
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