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"Climate Change AI Innovation Grants for Machine Learning Applied to Climate Mitigation, Adaptation and Climate Science" is currently closed and not accepting applications.
Climate Change AI's Innovation Grants are the most established dedicated funding line for machine learning applied to climate problems, and the program's defining requirement is worth understanding before writing a word of proposal: every funded project must produce a publicly available dataset, benchmark or simulator complying with FAIR Data Principles.
This is not a formality bolted onto a research grant - it is the program's theory of change. Climate Change AI's view is that the binding constraint on ML-for-climate work is not model architecture but the absence of usable, open data in domains like methane monitoring, grid operations, agricultural adaptation and ecosystem observation, and the grants exist to relieve that constraint.
Applicants proposing a modeling advance with no accompanying public data artifact are proposing the wrong thing.
Eligible topic areas span power and energy systems, agriculture and food security, disaster prediction and management, ecosystems and biodiversity, cities and urban planning, transportation, ocean and marine systems, low-carbon technology development, behavioral and social science approaches to climate action, and AI governance including assessment of AI's own emissions footprint.
Awards are typically up to $150,000 for one year, with institutional overhead capped at 10% - a tight indirect rate that makes the grants awkward for institutions with high negotiated rates and better suited to teams that can absorb administration cheaply. Competition is severe: a recent cycle drew over 400 submissions from institutions in 78 countries and funded 12 projects totaling roughly $1. 7 million.
Eligibility is narrower than the international applicant pool suggests - the Principal Investigator must be affiliated with an accredited university in an OECD member country and eligible to hold grants there, though co-investigators may come from any country or sector, which is the intended route for Global South collaboration.
Climate Change AI has indicated it does not currently have a further call of this program planned; researchers should monitor the calls page and contact partnerships@climatechange. ai, since the funder consortium (Quadrature Climate Foundation, Schmidt Futures, Google DeepMind, Global Methane Hub) has recurred across cycles and the program has restarted after gaps before.
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Or search similar grants →According to the current listing, eligibility includes: The Principal Investigator must be affiliated with an accredited university in an OECD member country and must be eligible to hold grants at that institution - faculty, postdoctoral researchers and research scientists all qualify. Co-investigators may be based in any country and in any sector, including nonprofits, startups, companies and governmental or intergovernmental organizations, making collaborative structures the standard route for participation by researchers outside OECD countries. Climate Change AI board members, staff and program chairs are not eligible to apply. Projects must leverage AI or machine learning to address climate change mitigation, adaptation or climate science, and every funded project must produce a publicly available dataset, benchmark or simulator complying with FAIR Data Principles. Institutional overhead is capped at 10% of the total project budget. Awards are typically up to $150,000 for a one-year period. The most recent cycle used a September 15 full proposal deadline; the funder has stated no further call is currently planned and directs interested partners to partnerships@climatechange.ai. Confirm the full requirements in the official notice before applying.
The current listing shows grants are typically up to $150,000 USD per project for a one-year project period. The most recent completed cycle awarded approximately $1.7 million USD in total across 12 projects. Institutional overhead is capped at 10% of the total project budget. Verify award ceilings, matching requirements, and allowable costs in the official notice.
The published deadline was September 15, 2026, which has passed. Check the official notice for any future application windows before investing time in a proposal.
Climate Change AI Innovation Grants for Machine Learning Applied to Climate Mitigation, Adaptation and Climate Science is funded by Climate Change AI, with funding from Quadrature Climate Foundation, Schmidt Futures, Google DeepMind and Global Methane Hub (fiscal sponsor Future Earth). 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.
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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.
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