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Climate Change AI Innovation Grants fund catalytic projects that apply machine learning to climate change mitigation, adaptation and climate science, with awards of up to 150,000 US dollars for one-year projects. The 2026 round awarded 1. 7 million dollars to 12 projects selected from more than 400 submissions spanning 78 countries.
Funding for that round came from the Quadrature Climate Foundation, Google DeepMind and the Global Methane Hub, with fiscal sponsorship from the Canada Hub of Future Earth; Schmidt Futures has supported earlier rounds.
Eligible topic areas are broad and include power and energy systems, agriculture and food security, disaster management, ecosystems and biodiversity, cities and urban planning, ocean and marine systems, transportation, and climate-related health applications.
The distinguishing requirement, and the one most likely to sink an otherwise strong proposal, is the open-data condition: Executive Director Dr Maria Joao Sousa has stated that funded teams must build a critical dataset as a digital public good supporting further innovation and must release open-source code. A project that depends on proprietary or licence-restricted data is structurally a poor fit.
Awards go to partnerships spanning academic researchers, non-profits, startups and other companies, and governmental or intergovernmental organisations, and past recipients sit at institutions across six continents. As of the last published update the programme listed no future call, so applicants should monitor the innovation grants page and contact partnerships at climatechange.
ai for notice of the next round rather than assume an annual cycle.
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Or search similar grants →According to the current listing, eligibility includes: Open internationally, with past awardees at institutions across six continents and, in the 2026 round, submissions from 78 countries. The programme funds partnerships that may involve academic researchers, non-profit organisations, startups and other companies, and governmental or intergovernmental organisations; some rounds have additionally required that the Principal Investigator be affiliated with an accredited university in an OECD member country, so applicants should confirm the PI-affiliation rule in the specific call text before building a consortium. Projects must apply AI or machine learning to climate change mitigation, adaptation or climate science, and must commit to producing a dataset released as a digital public good and to publishing open-source code; teams whose data is proprietary or licence-encumbered should not apply. Award size is up to 150,000 US dollars over twelve months. Acceptance is highly competitive at roughly 3 percent in the 2026 round, so the practical advice is to propose a single well-scoped deliverable with a clearly identified dataset gap rather than a broad research programme. No open call was listed as of the latest published page; prospective applicants should watch climatechange.ai/innovation_grants and write to partnerships@climatechange.ai to be notified when the next round opens. Confirm the full requirements in the official notice before applying.
The current listing shows individual grants are up to 150,000 US dollars for one year of work, so amount_min and amount_max are both set to 150,000 because the programme publishes a single ceiling rather than a range. The 2026 round distributed 1.7 million dollars across 12 projects, which implies an average award close to the 150,000 dollar ceiling rather than well below it, so applicants should scope to roughly that figure rather than hoping for more. Since inception the programme has committed 4.9 million dollars across 34 projects involving researchers at 97 institutions in 26 countries. The selectivity is the number that should drive the decision to apply: the 2026 round drew over 400 submissions from 78 countries for 12 slots, a success rate near 3 percent. At 150,000 dollars for twelve months this is a seed instrument, not a programme-building one, and the realistic use is to fund a focused dataset build plus a demonstration model rather than a multi-year research agenda. Verify award ceilings, matching requirements, and allowable costs in the official notice.
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 the Quadrature Climate Foundation, Google DeepMind and the Global Methane Hub, fiscally sponsored by the Canada Hub of 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.
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.
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