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The Chan Zuckerberg Initiative (CZI) invites proposals to build large-scale AI and machine learning models for the biological sciences through competitive allocations on CZI's GPU cluster of 1,024 NVIDIA H100 GPUs in an NVIDIA DGX SuperPOD configuration with VAST fast data storage. The program targets foundation model development for biology, virtual cells, and disease research.
Priority is given to projects aligned with CZI's Virtual Cell initiative and the broader mission to cure, prevent, or manage all diseases by the end of the century. The cluster is optimized for AI/ML training at scale, with applications evaluated on rolling deadlines until full cluster allocation is reached.
Recipients receive a minimum allocation of 96 GPUs as an in-kind award, enabling training of foundation models that would otherwise be financially prohibitive through conventional university resources. Approved projects integrate with CZI's growing virtual cell ecosystem alongside partner institutions including the Broad Institute, Allen Institute, Arc Institute, and Wellcome Sanger Institute.
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Search similar grants →Based on current listing details, eligibility includes: Principal Investigators and Co-PIs must hold faculty or equivalent independent investigator status at U.S.-based nonprofit institutions including colleges, universities, hospitals, independent research labs, and government agencies. For-profit entities are ineligible. Meta employees are prohibited from applying. Applicants must commit to using minimum 96 GPU utilization during training phases and align with CZI's biomedical mission. Strong preference for projects building foundation models, virtual cell models, or large-scale AI systems advancing biological discovery. Applicants should confirm final requirements in the official notice before submission.
Current published award information indicates In-kind GPU compute allocation on CZI's cluster of 1,024 NVIDIA H100 GPUs in a DGX SuperPOD configuration. Minimum allocation of 96 GPUs per project for training large-scale biological AI models. No cash funds awarded; the in-kind value of allocations ranges from approximately $250,000 to several million USD depending on GPU-hour usage and project duration. Always verify allowable costs, matching requirements, and funding caps directly in the sponsor documentation.
The current target date is June 18, 2026. Build your timeline backwards from this date to cover registrations, approvals, attachments, and final submission checks.
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Accelerating and Scaling Biological Sciences with AI is sponsored by Chan Zuckerberg Initiative (CZI). CZI invites proposals to build large-scale AI/ML models that cannot be created with conventional university resources, utilizing CZI's high-performance computing cluster optimized for AI and machine learning training at scale. The grant is for an allocation of GPU resources.
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The Chan Zuckerberg Initiative (CZI) Accelerating and Scaling Biological Sciences via AI program provides competitive GPU compute allocations on CZI's high-performance cluster to support large-scale AI and machine learning model building for biological discovery. The cluster features 1,024 NVIDIA H100 GPUs in a DGX SuperPOD configuration with VAST fast data storage. Researchers receive a minimum allocation of 96 GPUs to build foundation models and large-scale AI systems that power new approaches to understanding biology. Priority is given to models aligned with CZI's Virtual Cells initiative, but all proposals relating to CZI's mission to cure, prevent, or manage all diseases by the end of the century are considered. This is an in-kind award with no cash funds, representing CZI's broader commitment of at least $10 billion to basic scientific research over the coming decade. The program reflects the growing recognition that compute access is a critical bottleneck for AI-driven biological research and positions CZI as a major enabler of AI for biomedical science.
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