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Search verified grants from Cooperative AI Foundation, Google DeepMind, Schmidt Sciences, UK Advanced Research and Invention Agency (ARIA), and Google.org →Cooperative AI Research Grants is sponsored by Cooperative AI Foundation, Google DeepMind, Schmidt Sciences, UK Advanced Research and Invention Agency (ARIA), and Google.org. A technical research funding call for researchers worldwide, focusing on the study of how large-scale multi-agent AI systems behave as a group, and how to provide frameworks to understand and mitigate potential risks.
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Google DeepMind and partners announce multi-agent safety research funding call. — Google DeepMind June 11, 2026 Responsibility & Safety Investing in multi-agent AI safety research Google DeepMind, Schmidt Sciences, the Cooperative AI Foundation, ARIA and Google. org Scaling AI Safety Research for a Multi-Agent World For the past decade, we’ve focused on making individual AI models more capable, helpful and safe.
Today, Google DeepMind — together with Schmidt Sciences , the Cooperative AI Foundation , the Advanced Research and Invention Agency , and supported by Google. org — is announcing a new technical research funding call of up to $10M for researchers worldwide. As AI technology scales, we’re entering a new era.
Soon, millions of AI agents — built by different organizations — will interact across digital environments, communicating, negotiating and transacting with one another. When these systems interact, they must do so safely and predictably. This shift creates a vital opportunity: we can strengthen the safety and stability of the entire AI ecosystem from the very beginning.
The funding call focuses on the study of how large-scale multi-agent AI systems behave as a group, and how we can provide frameworks to understand and mitigate against potential risks. By empowering researchers globally, we aim to solve the “invisible” safety risks that arise when independent systems interact across different networks.
Why the agent ecosystem matters When large groups of AI agents interact, new collective behaviors and capabilities can emerge suddenly. Currently, we lack the tools to predict, measure and monitor these transitions. Most safety evaluations analyze models in isolation.
However, as we and others have previously argued, interacting autonomous agents can produce complex, "emergent" behaviors that are difficult to anticipate. Because this is a new area of research, it is critical to understand how these shifts occur. For example, could they cause an unpredictable flurry of economic activity or lead to new security challenges?
Understanding how to manage these system-wide behaviors is our core objective. Scaling the frontier of multi-agent safety research Although foundational frameworks for multi-agent safety exist, the rapid evolution of these systems requires an immediate, large-scale expansion of research.
Our 2025 research established a framework for understanding these interactions, while our recent work on AI Agent Traps explores vulnerabilities agents face in adversarial environments. Now, we must move faster. We are at a critical juncture where the complexity of multi-agent interactions is outpacing existing safety models.
This funding call aims to accelerate progress by supporting a global network of independent researchers. A diverse community is essential to ensure safety standards are transparent and robust for everyone.
This effort also advances the mission of Schmidt Sciences’ Science of Trustworthy AI and AI Agents programs, which support foundational work on understanding and mitigating risks from frontier AI systems, as well as ARIA’s Scaling Trust programme, which seeks to unlock new forms of cyber-physical multi-agent coordination. A collaborative call to action No single lab can solve multi-agent safety alone.
We invite academic and independent researchers to submit proposals in four priority areas: Sandboxes and testbeds: Building realistic, reproducible environments to evaluate, compare and accelerate progress across all areas of multi-agent safety. This includes virtual marketplaces, simulated ecosystems and multi-organisation workflows.
The science of agent networks: Understanding the safety-relevant properties of interacting agent populations, including investigating how collective capabilities emerge and scale, how networks fail or become volatile and how to detect dangerous, unexpected population-level properties.
Strengthening agent infrastructure: Stress-testing the protocols for identity, reputation and commitment that are secure cross-platform agent interactions. Oversight and control: Developing methods to monitor deployed agent populations and mitigate collective harms at scale. We invite researchers to review our call for proposals and join us in building a safe foundation for a multi-agent future.
The deadline to apply is August 8, 2026, with awardees expected to be announced in Autumn 2026. For more details on technical requirements and the application process, visit our application portal .
According to the current listing, eligibility includes: Researchers and early-career researchers, with projects typically carried out by a single individual for the early-career track. Confirm the full requirements in the official notice before applying.
The current listing shows up to $10,000,000 (total across all awards), with an Early-Career Track up to GBP 100,000 (approximately $127,000 USD). Verify award ceilings, matching requirements, and allowable costs in the official notice.
Applications for Cooperative AI Research Grants are due August 7, 2026. Build your timeline backwards from this date to cover registrations, approvals, and final submission checks.
Cooperative AI Research Grants is funded by Cooperative AI Foundation, Google DeepMind, Schmidt Sciences, UK Advanced Research and Invention Agency (ARIA), and Google.org. Verify program details on the funder's official page before applying.
This listing is flagged as international in scope. Check the official notice for country-specific restrictions before applying.
NVIDIA Graduate Fellowship Program is a grant from NVIDIA providing up to $60,000 per award to PhD students conducting research that advances accelerated computing and its applications. Now in its 25th year, the program invites nominations from doctoral students pushing the boundaries of artificial intelligence, robotics, autonomous vehicles, and related fields. Recipients receive not only research funding but also access to NVIDIA technology, products, and engineering expertise, along with a mandatory in-person summer internship. Students are nominated by their faculty advisors and selected based on academic achievement and research area alignment.
CalSEED Concept Award is a grant from the California Energy Commission that provides $150,000 in funding to early-stage clean energy innovators in California. The program targets individuals, businesses, and nonprofits developing hardware, software, or integrated solutions at Technology Readiness Levels 2-4. Eligible technology areas rotate each cycle and have included battery recycling and reuse, long-duration energy storage, medium- and heavy-duty vehicle electrification, industrial electrification, and advanced EV charging. Applicants must be located in California, have under $1 million in private funding, and propose innovations that benefit California ratepayers. Concept Award winners also receive professional development resources and access to accelerator programs, and may compete for a subsequent $450,000 Prototype Award.
NIST SBIR Phase I - Advanced Manufacturing and Robotics is sponsored by National Institute of Standards and Technology. NIST SBIR Phase I - Advanced Manufacturing and Robotics is a grant from the National Institute of Standards and Technology (NIST) that funds small businesses with innovative research and technology ideas in advanced manufacturing and robotics.
Schmidt Sciences' 2026 Science of Trustworthy AI RFP closes May 17 with two funding tiers — up to $1M (Tier 1) and $1–5M+ (Tier 2) over 1–3 years, with a 10% indirect cost cap. The three research aims target misalignment under distribution shift, predictive-validity evaluations, and oversight of superhuman systems. Here is why the structure favors team-based proposals.
Read articleGoogle.org is offering up to $3 million per organization across two AI challenges — one for government innovation, one for scientific breakthroughs. Eligibility, strategy, and what wins.
Read articleThe Google.org AI for Government Innovation Challenge offers $1-3M grants with an April 3 deadline. But it is part of a larger shift: tech philanthropy is becoming the R&D lab for public sector innovation.
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