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CZI's Accelerating and Scaling Biological Sciences with AI RFA provides allocations of high-performance GPU compute to researchers building large-scale AI/ML models for the biological sciences that cannot be created with conventional university resources.
Awardees receive an in-kind allocation (minimum 96 GPUs) on CZI's CoreWeave-hosted cluster of 1,024 Nvidia H100 GPUs in a DGX SuperPod configuration with VAST fast data storage and a fully managed Kubernetes environment, for projects up to one year. No cash funds are provided.
Priority goes to projects aligned with CZI's virtual cell work, though all proposals advancing CZI's mission to cure, prevent, or manage all diseases are considered. Awards require open-science and code-sharing commitments (permissive licenses), de-identified data only, and rolling review.
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Or search similar grants →According to the current listing, eligibility includes: U.S.-based nonprofit organizations only, including colleges, universities, hospitals, laboratories, and governmental agencies. All PIs/Co-PIs must hold faculty or equivalent independent investigator status at U.S. nonprofit institutions. Meta employees are ineligible. Applications submitted via CZI's portal on a rolling basis until the cluster is fully allocated. Confirm the full requirements in the official notice before applying.
The current listing shows in-kind allocation of GPUs on CZI's cluster of 1,024 Nvidia H100 GPUs (minimum request of 96 GPUs) for up to one year; no cash is awarded. Estimated in-kind compute value ranges from roughly $2 million (96 GPUs for one year) up to about $20 million for the largest allocations. Verify award ceilings, matching requirements, and allowable costs in the official notice.
Chan Zuckerberg Initiative Accelerating and Scaling Biological Sciences with AI RFA (GPU Cluster Allocation) is funded by Chan Zuckerberg Initiative (CZI). Verify program details on the funder's official page before applying.
Start from the official opportunity page linked in this listing — it carries the sponsor's submission instructions.
The AI Safety Policy Entrepreneurship Fellowship is FAS's route for turning technical and domain expertise into frontier AI safety policy that actually moves. It is a part-time hybrid programme running 30 September 2026 to 28 February 2027, with applications due 7 September 2026, and it pays a USD 5,000 stipend plus up to USD 1,000 as a merit award. Fellows commit roughly five hours a week to developing a policy memo on a specific AI safety challenge, attend training sessions, join an in-person retreat in California from 4 to 7 November 2026, and present at a capstone event in Washington DC during the week of 22 February 2027. The design target is explicit and unusual: it recruits early- to mid-career professionals who have limited direct public policy experience but deep expertise elsewhere - technical AI research, academia, think tanks, civil society, industry, law, cybersecurity and national security - and teaches them the mechanics of getting an idea adopted. Selection weighs clear understanding of AI governance challenges, concrete implementation-oriented solutions rather than broad principles, awareness of which stakeholders must be moved, and a credible commitment to translating expertise into policy outcomes. Because the stipend is modest and the time commitment part-time, this is designed to sit alongside an existing job rather than replace one.
The Climate Change AI Innovation Grants program supports projects that address research and deployment challenges in climate change mitigation, adaptation, and climate science by leveraging AI and machine learning, while also creating publicly available datasets and tools to catalyze further work. The program enables key partnerships that accelerate the research-to-deployment cycle, creating synergies between academic researchers, nonprofits, startups and other companies, and governmental or intergovernmental organizations. Funded by the Quadrature Climate Foundation, Schmidt Futures, and Google DeepMind, with Future Earth serving as fiscal sponsor, this is one of the few dedicated grant programs specifically targeting the intersection of AI/ML and climate change. Projects typically involve climate modeling, weather prediction, emissions monitoring, energy optimization, biodiversity monitoring, and other environmental applications of machine learning. The 2026 competition opens with a full proposal deadline of September 15, 2026. The program has grown steadily since its inception, funding 23 projects to date across diverse climate domains and geographies.
The Climate Change AI Innovation Grants program supports catalytic projects using AI and machine learning for climate action, funding research and deployment challenges in climate change mitigation, adaptation, and climate science. Projects must create publicly available datasets and tools as digital public goods, and release open-source code. The program builds partnerships between academic researchers, non-profits, startups, companies, and governmental organizations to accelerate the research-to-deployment cycle. Past funded projects span climate modeling, emissions monitoring, renewable energy optimization, and disaster prediction across all continents.