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The Chan Zuckerberg Initiative (CZI) invites proposals to build large-scale AI/ML models for biology that cannot be created with conventional university computing resources. The RFA provides an in-kind allocation of CZI's GPU cluster (minimum request of 96 GPUs) rather than cash, supporting the training of large biological foundation models and other compute-intensive AI-for-science research.
The program is part of CZI's expanded AI-powered biomedical science strategy aimed at helping cure, prevent, or manage all diseases.
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Or search similar grants →According to the current listing, eligibility includes: Researchers at universities and nonprofit research institutions building large-scale AI/ML models in biology that require compute beyond typical academic resources; applicants request an allocation of at least 96 GPUs. Confirm the full requirements in the official notice before applying.
The current listing shows in-kind award of CZI GPU compute resources (minimum request of 96 GPUs); no cash funds, financial contributions, or fees are associated with the award. Verify award ceilings, matching requirements, and allowable costs in the official notice.
Chan Zuckerberg Initiative AI Meets Biology GPU Compute Research RFA 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.
CIFAR and the Canadian AI Safety Institute fund Catalyst Project proposals addressing sociotechnical considerations in AI safety. The program supports interdisciplinary research in machine learning applications to science and society, with recent funded projects spanning misinformation combat, trustworthy language models, democratic alignment of AI systems, Indigenous AI governance, and real-world safety in autonomous systems. Designed to catalyze new research areas and collaborations at the intersection of social sciences, humanities, and AI safety.
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.