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In 2012, a three-person team at the University of Toronto trained a neural network called AlexNet on two NVIDIA GTX 580 GPUs. The compute cost roughly $1,000. That work—funded by an NSERC grant and a Google Faculty Research Award—triggered the deep learning revolution. Today, training a frontier model can exceed $100 million.
The global pool of competitive AI funding now exceeds $30 billion annually. The U.S. federal government alone invested approximately $3.3 billion in non-defense AI R&D in FY2025, and the Department of Defense requested $13.4 billion for AI and autonomy in FY2026. Most of this funding goes to researchers who found it first—not researchers who deserved it most.
If you are a researcher in any field—biology, climate science, education, materials science, public health—who is integrating machine learning or AI methods into your work, this guide is written for you. Not for computer scientists. For the domain experts who are building the applications that actually matter.
| Your Field | Start Here | Also Check |
|---|---|---|
| Biomedicine & Health | NIH AI programs (Bridge2AI, NIBIB) | NSF BIO, SBIR Phase I |
| Climate & Environment | DOE AI for Science, AI Climate grants | NSF GEO, NOAA, Bezos Earth Fund |
| Agriculture & Food | USDA NIFA ($104M AI allocation) | NSF-USDA joint institutes |
| Defense & Security | DARPA BAAs (I2O, DSO, BTO) | IARPA, DOD CDAO, SBIR |
| Education & Workforce | NSF ExpandAI, Dept. of Education | Humanity AI coalition, IES |
| Materials & Engineering | DOE Genesis Mission, NSF ENG DCL | NIST, NSF MPS |
| AI Startup / Commercialization | NSF SBIR/STTR (20% success rate) | NIH SBIR, DOE SBIR, NVIDIA grants |
| AI Safety & Ethics | Open Philanthropy ($50M+/yr) | NSF SLES, Humanity AI, NIST CAISI |
DARPA
$314M core AI
I2O BAA, DSO BAA, BTO BAA, AI Forward, Young Faculty Award
Browse DARPA AI programs →DOE
$320M+ Genesis Mission
AI for Science, ModCon, 14 robotics projects, 37 foundational AI awards
Browse DOE AI grants →Four agencies dominate federal AI funding, but each operates with radically different priorities, review timelines, and success rates. Understanding these differences is the highest-leverage thing you can do before writing a word of your proposal.
NSF's flagship National AI Research Institutes program now funds 27 institutes across 40+ states, with five-year awards typically in the $16–20 million range. In July 2025, a $100 million infusion—co-funded by Capital One and Intel—stood up five new institutes and a community hub.
But the institutes are just the visible tip. NSF's CISE directorate funded 22% of proposals in FY2024 through programs like Safe, Trustworthy, and Responsible AI (SLES). The Engineering Directorate's Dear Colleague Letter for AI research opens doors for proposals that fall between disciplinary cracks—materials scientists using ML for alloy discovery, civil engineers deploying computer vision for bridge inspection, chemical engineers optimizing reactor design with reinforcement learning. If your work touches AI but you don't consider yourself an AI researcher, NSF's engineering DCL is probably your best entry point.
A program most applicants miss: the CISE Research Initiation Initiative (CRII), which provides $175,000 over two years to early-career researchers at non-R1 institutions. It is explicitly designed for investigators who lack the preliminary data and lab infrastructure that larger grants demand. For tenure-track faculty, the NSF CAREER Award remains the gold standard for AI researchers building their labs.
You do not pitch your idea to DARPA. You respond to a specific technical challenge that a program manager has spent months defining. The Information Innovation Office (I2O) runs a rolling Broad Agency Announcement covering proficient AI, resilient systems, and cyber operations. The Defense Sciences Office and Biological Technologies Office have their own BAAs that frequently include AI components.
What makes DARPA unique is speed. AI Exploration (AIE) opportunities use streamlined contracting to achieve a start date within three months of announcement. Performers then have 18 months to establish feasibility. Compare that to NSF's 6–12 month timeline from submission to award. The 2025 Young Faculty Award specifically targets early-career researchers at U.S. institutions, providing both funding and mentorship.
NIH does not have a single “AI grants” program. Instead, AI permeates virtually every institute and center, making it simultaneously the largest and hardest-to-navigate source of AI research funding. The reported $309 million in core AI R&D dramatically undercounts the real investment when you include bioinformatics, computational biology, and clinical decision support.
Bridge to Artificial Intelligence (Bridge2AI), funded at $130 million over four years through the NIH Common Fund, represents the most deliberate AI investment—it funds interdisciplinary teams to generate ethically sourced, AI-ready datasets in voice biomarkers, cell morphology, and clinical decision-making. The AIM-AHEAD program targets institutions underrepresented in AI research. NIBIB funds AI for medical image analysis. The National Institute on Aging supports AI Technology Collaboratories for elderly care.
The key insight for domain scientists: NIH program officers want to fund the science, not the method. A cancer biologist using graph neural networks for drug-target interaction prediction is more competitive than a computer scientist proposing the same network architecture without the biological question. The R01 success rate sat at roughly 22% in FY2024, but early-career rates dropped to 18.5% in FY2025 due to budget disruptions. Less competitive mechanisms—R21 exploratory grants, SBIR/STTR (where NIH success rates exceed 20%)—all welcome AI-powered approaches.
DOE announced over $320 million for its Genesis Mission in 2025—the largest single-year AI commitment in the agency's history. The investment spans a Transformational AI Models Consortium building self-improving models for science; 14 projects in robotics, automated laboratories, and autonomous experiments; and 37 foundational AI awards for data curation and model development. Congress appropriated $150 million through September 2026, with 24 collaboration agreements including Google DeepMind.
DOE's comparative advantage is infrastructure. The agency operates the most powerful supercomputers on Earth—Aurora at Argonne, Frontier at Oak Ridge—and provides researchers access through allocation programs. For researchers whose work requires massive compute—training scientific foundation models, running molecular dynamics simulations, optimizing fusion reactor designs, or processing petabytes of climate data—DOE is often the only realistic funding path.
USDA's National Institute of Food and Agriculture received a $104 million AI allocation in FY2025 and co-funds NSF AI Research Institutes focused on agriculture. NIST launched the Center for AI Standards and Innovation (CAISI, formerly the AI Safety Institute) with $50 million and stood up $20 million in Centers for AI in Manufacturing. The DOD Chief Digital and AI Office grew from $10 million in FY2022 to $140 million in FY2025. Even agencies without dedicated AI programs—EPA, NOAA, the Department of Education—co-fund AI-related research through joint solicitations with NSF.
American researchers routinely leave international money on the table. Many of the world's largest AI funding programs explicitly welcome U.S. participants as consortium partners, and the dollar amounts rival anything available domestically.
EU Horizon Europe adopted a €14 billion work programme for 2026–2027, with AI as a cross-cutting priority. The GenAI4EU initiative has grown to nearly €700 million. The RAISE initiative has €107 million earmarked for foundation models in materials science and climate, with a €30 million call for foundation model development opening Q1 2026. U.S. institutions can participate as consortium members—they don't receive EU funding directly, but their involvement strengthens the proposal and they share in research infrastructure and data access. The mechanism: find a European lead partner, join their consortium, and your institution covers your own costs (often through a parallel NSF or DOE award).
The UK committed £1.6 billion in targeted AI funding through UKRI from 2026 to 2030—their largest single investment area. Initial priorities include £137 million for AI-enabled drug discovery and Turing AI Pioneer Fellowships worth up to £2.19 million each. Japan has pledged 10 trillion yen ($65 billion) in government funding through 2030 and quadrupled its chips-and-AI budget to ¥1.23 trillion ($7.9 billion) in FY2026. RIKEN's AIP Center and JST fund international collaborations. South Korea's AI budget stands at &won;0.88 trillion (~$640 million) for 2025, with a threefold increase proposed for 2026. Singapore committed S$1 billion to its National AI R&D Plan over five years and runs targeted bilateral grant calls with Korea and Israel, typically funding $500K–$1.2M per project.
Browse EU AI funding →The most significant development in AI funding in the past two years is the emergence of philanthropic coalitions operating at government scale. Humanity AI, announced in 2025, pools $500 million from ten foundations—MacArthur, Ford, Mellon, Mozilla, Omidyar Network, Packard, Doris Duke, Lumina, Kapor, and Siegel Family Endowment. The coalition targets five priority areas: advancing democracy, strengthening education, protecting artists, enhancing work, and defending personal security. Pooled-fund grants begin in 2026.
Open Philanthropy committed roughly $50 million to technical AI safety research in 2024 and launched a $40 million RFP covering 21 research directions—essentially a roadmap for the field. If you work on alignment, interpretability, or AI governance, Open Philanthropy is likely your most efficient funding path. OpenAI's People-First AI Fund distributed $40.5 million in unrestricted grants to 208 U.S. nonprofits, with nearly 3,000 applicants. It targets organizations with operating budgets between $500,000 and $10 million.
Search our foundation directory to find funders by focus area, giving level, and geography. Corporate programs run on different timelines. NVIDIA's Academic Grant Program provides H100 GPU hours and DGX Spark supercomputers—no cash, but compute that would cost six figures on the open market. Amazon Research Awards provide up to $70,000 plus $50,000 in AWS credits per PI. Microsoft's AFMR grants up to $20,000 in Azure credits with a dedicated program for HBCUs and Hispanic-serving institutions. Google, Amazon, and NVIDIA all run 4–8 week review cycles—compare that to 6–12 months for federal agencies. The tradeoff: faster decisions, fewer compliance burdens, but potential restrictions on publication or IP. Read the terms carefully.
NSF's CISE directorate funded 22% of proposals in FY2024. NSF Engineering funded 23%. NIH R01 grants succeeded at roughly 22% overall in FY2024, though early-career rates dropped to 18.5% in FY2025 amid budget disruptions. SBIR Phase I awards land at 17–20% across agencies, with NSF running the highest rate. SBIR Phase II jumps to approximately 60%—the best odds in federal grantmaking, if you can clear Phase I. See our success rate data for detailed breakdowns by agency and program.
Timeline planning: Federal grants require 6–18 months from conception to award. NSF proposals typically take 6–9 months from submission to decision. NIH runs three standard receipt dates per year (February, June, October) with 9–12 month review cycles. DARPA moves faster —3–6 months for AIEs. Foundation and corporate grants run 4–12 weeks. If you need funding in 12 months, you should be submitting federal proposals now while pursuing foundation funds as bridge financing.
Before writing a single word, call the program officer. This is not optional. Every agency expects it, and program officers will tell you directly whether your idea fits their portfolio. A 15-minute phone call can save you three months of wasted effort.
Common mistakes that kill AI proposals: leading with the technology instead of the problem it solves; claiming novelty without citing the state of the art; proposing a system without a clear evaluation plan; underestimating the budget for compute, data labeling, and IRB compliance; and neglecting Broader Impacts (NSF) or diversity statements (NIH). Reviewers reject more proposals for poor fit than for poor science.
How to Write a Winning AI Grant Proposal
Fundamentals of structuring compelling AI research proposals
AI Grant Budget Templates
Budget justification for GPU compute, data labeling, and cloud costs
AI Grant Resubmission Strategies
How to respond to reviewer feedback and strengthen your proposal
Writing AI Ethics Sections
Responsible AI and governance sections reviewers want to see
NSF CAREER Award Guide
The most prestigious early-career award for AI researchers at universities
How to Respond to a DARPA BAA
Navigate DARPA's unique proposal process and win defense AI contracts
Grant funding is only half the equation. Several programs provide the compute, data, and infrastructure that AI research demands—often at zero cost. Our complete guide to GPU credits and compute allocations covers every program in detail.
NAIRR
NSF-led pilot connecting 600+ research teams to shared AI infrastructure. Rolling proposals accepted. Eligibility: universities, nonprofits, federal labs, tribal agencies, startups with federal grants.
DOE INCITE & ALCC
81 projects awarded supercomputer time in 2025 across Aurora and Frontier. Millions of node-hours at no cost. 2026 Call for Proposals is open.
NSF ACCESS
Free supercomputing for any U.S. researcher or educator—with or without an existing grant. Four tiers from Explore to Maximize. ML and data science workloads welcome.
Cloud Research Credits
AWS, Google Cloud, and Azure run academic credit programs providing $5,000–$100,000 in compute. Typically non-competitive—apply and receive credits.
Stack these programs. A well-funded AI research group might hold an NSF award for personnel, an INCITE allocation for large-scale training, NAIRR access for datasets, cloud credits for deployment testing—each at zero dollars beyond the time to apply.
New AI funding opportunities, deadline alerts, and grant writing tips every Tuesday.
The AI grants landscape shifts every week. New solicitations drop, deadlines move, agencies restructure priorities. Granted tracks AI funding across every source covered in this guide—search by sub-field, eligibility, deadline, and funding level. Check grants closing soon or recently added opportunities to stay current. For a complete overview of how to navigate this landscape, see our AI researchers hub. For teams building AI-powered research workflows, our MCP server lets your AI assistant query the database directly, and the weekly newsletter delivers curated opportunities every Tuesday.
In 2012, AlexNet needed $1,000 and one grant. Your next breakthrough may need considerably more. The funding exists. The question is whether you find it before your competitors do.
Data sources: NITRD FY2025 Supplement, NSF funding rates, NIH Reporter, DOE press releases, EU Horizon Europe work programme. Last verified February 2026.
Cross-Border Cyber Hubs is sponsored by European Commission — Digital Europe Programme. Expected Outcome: World-class Cross-Border Cyber Hubs across the Union for pooling data on cybersecurity threats between several Member States, equipped with a highly secure infrastructures and advanced data analytics tools for detecting, gathering and storing data on cybersecurity threats, analysing this data, and sharing and reporting CTI, reviews and analyses. Sharing of Threat Intelligence between National Cyber Hubs, and information sharing agreements with competent authorities and networks, including CSIRTs. Objective: The former Cross-border SOC platforms were financed during previous calls and such collaboration is envisaged for the Cross-Border Cyber Hubs. They should provide new additional capacity building upon and complementing existing SOCs/Cyber Hubs, Computer Security Incident Response Teams (CSIRTs), ISACs and other relevant actors. This action is aimed mainly at new Cross-Border Cyber Hubs. Supporting activities for the SOCs that were already launched under the previous DIGITAL work programmes (2021-2022 and 2023-2024) 1 could also be included when relevant to ensure collaboration with the Cross-Border Cyber Hubs. In addition to setting up processes, tools and services for prevention, detection and analysis of emerging cyberattacks, the scope also covers the acquisition and/or adoption of common (automation) tools, processes and shared data infrastructures for the management and sharing of contextualised and actionable cybersecurity operational information across the EU. Well-established open standards for CTI sharing (e.g. MISP Standard 2 ) or automation of advisory information (e.g. CSAF 3 ) and cybersecurity related messages (e.g. by IntelMQ) should be considered. Cross-Border Cyber Hubs could also foresee the possibility to monitor undersea infrastructure, such as submarine cables. 1 ENSOC and ATHENA consortia are already financed. 2 MISP Standard: https://www.misp-standard.org/. 3 Common Security Advisory Framework (CSAF): Machine-processable format enables automated database reconciliation - https://www.bsi.bund.de/EN/Themen/Unternehmen-und-Organisationen/Informationen-und Empfehlungen/Empfehlungen-nach-Angriffszielen/Industrielle-Steuerungs-und Automatisierungssysteme/CSAF/CSAF_node.html. Scope: The Cross-Border Cyber Hubs platforms will contribute to enhancing and consolidating collective situational awareness and capabilities in detection and CTI, supporting the development of better performing data analytics, detection, and response tools, through the pooling of large amounts of data, including new data generated internally by the consortia members. The platforms should act as a central point allowing for broader pooling of relevant data and CTI, enabling the dissemination of threat information on a large scale and among a large and diverse set of actors (e.g. CERTs/CSIRTs, ISACs, operators of critical infrastructures). According to the Cyber Solidarity Act, the Cross-Border Cyber Hubs and the CSIRTs Network shall cooperate closely, in particular for the purpose of sharing information. To that end, they shall agree procedural arrangements on cooperation and sharing of relevant information and on the types of information to be shared. Furthermore, Cross-Border Cyber Hubs could also deploy solutions for the surveillance and protection of critical undersea infrastructure, such as submarine cables, and the detection of malicious activities around them, to improve the resilience and security of this infrastructure, which is critical for global communications. The response to such hybrid threats could also include situational awareness performed through the collection and analysis of in-situ, sea based sensor data as well as relevant satellite imagery. For this activity, operational synergies with the EU Copernicus Space Programme and in particular with its Security Service are required. Where the Cross-Border Cyber Hubs obtain information relating to a potential or ongoing large-scale cybersecurity incide Programme areas: DIGITAL Keywords: Artificial intelligence, Capacity building, Cyber-physical systems, Cybersecurity, Cybersecurity Domains, Defence, Real time data analytics, TSI (Technical Specifications for Interoperability), Cross-Border Cyber Hubs, cyber threats detection, information sharing, preparedness and resilience of critical infrastructures, response to cyber threats, submarine cable security
The ARPA-H CIRCLE (Critical Illness Immunological Reprogramming and Control Point Learning Engine) program aims to develop AI-driven digital twin capabilities for treating critical illness in ICU patients. Clinicians currently lack tools to track rapidly changing immune responses where excessive inflammation can cause organ failure and death. CIRCLE seeks to create computational models of individual immune systems that provide actionable insights and enable better deployment of existing and next-generation immunotherapies for critically ill patients. The program addresses three technical areas: creating datasets characterizing critical illness progression in real time; developing patient-specific digital twin computational immune system models using AI/ML; and testing immune system modulation approaches with individualized treatment strategies. Solution summaries are due March 30, 2026, with full proposals due May 28, 2026. Teams may include academic institutions, non-profits, corporate entities, or combinations. This is a currently open solicitation posted on SAM.gov.
National Cyber Hubs is sponsored by European Commission — Digital Europe Programme. Expected Outcome: World-class National Cyber Hubs across the Union, supported by state-of-the-art technology, acting as clearing houses for detecting, gathering and storing data on cybersecurity threats, analysing this data, and sharing and reporting CTI, reviews and analyses, taking into account well-established standards for sharing and automation processes. Threat intelligence and situational awareness capabilities and capacity building supporting strengthened collaboration between cybersecurity actors, including private and public actors. Targeted training courses on the basis of the ECSF to improve the capacity of cyber security roles. • Applications for automated notification of private and public actors about compromised or insecure systems Objective: Where a Member State decides to participate in the European Cybersecurity Alert System, it shall designate or, where applicable, establish a National Cyber Hub, a single entity acting under the authority of the Member State. National Cyber Hubs have the capacity to act as a reference point and gateway to other public and private organisations at national level for collecting and analysing information on cyber threats and incidents and to contribute to a Cross-Border Cyber Hub. They are capable of detecting, aggregating, and analysing data and information relevant to cyber threats and incidents, such as cyber threat intelligence, by using in particular state-of-the-art technologies, and with the aim of preventing incidents. For the following programming cycle, the emphasis is on continuation of activities initiated during past years. The objective is to create or strengthen National Cyber Hubs, with state-of-the-art tools for monitoring, understanding and proactively managing cyber events, in close collaboration with relevant entities such as CSIRTs, ISACs, etc. They will also, where possible, benefit from information and feeds from other Cyber Hubs in their countries and use the aggregated data and analysis to deliver early warnings to targeted critical infrastructures on a need-to-know basis. National Cyber Hubs could also consider the possibility of monitoring undersea infrastructure, such as submarine cables. Scope: The aim is to build capacity for new or existing National Cyber Hubs, e.g. equipment, tools, data feeds, as well as costs related to data analysis, interconnection with Cross-Border Cyber Hubs, etc. This can include for example automation, analysis and correlation tools and data feeds covering Cyber Threat Intelligence (CTI) at various levels, ranging from field data to Security Information and Event Management (SIEM) data to higher level CTI. Automation is a key aspect in the efficient handling and processing of information. Where available, already established standards should be used, such as the Common Security Advisory Framework (CSAF) 1 , for security advisories or for collecting and processing cybersecurity-related messages (e.g. IntelMQ project 2 ). Applications developed by Cyber Hubs/SOCs should be compatible with European standardisation projects like the EU vulnerability database (EUVD). National Cyber Hubs should also leverage state-of-the-art technology such as artificial intelligence and dynamic learning of the threat landscape and context. This also includes the use of shared cybersecurity information, to the extent possible based on existing taxonomies and/or ontologies, and hardware to ensure the secure exchange and storage of information. The operations should be built upon live network data and other training data required in the initial phases. Where relevant, consideration should be given to SMEs as the ultimate recipients of cybersecurity operational information. A key element is the translation of advanced AI, data analytics and other relevant cybersecurity tools from research results to operational tools, and further testing and validating them in real conditions in combination with access to supercomputing facilities (e.g. to boost Programme areas: DIGITAL Keywords: Artificial intelligence, Capacity building, Cyber-physical systems, Cybersecurity, Cybersecurity Domains, Defence, Real time data analytics, TSI (Technical Specifications for Interoperability), National Cyber Hub, cyber threats detection, information sharing, preparedness and resilience of critical infrastructures, response to cyber threats, submarine cable security
241 matching grants · showing 30
SBIR/STTR Programs (Defense Health Agency) is sponsored by Department of Defense (DOD) - Defense Health Agency (DHA). The DHA SBIR/STTR Programs fund biomedical and health-focused technologies that enhance medical readiness, clinical care delivery, force health protection, operational medicine, and military healthcare modernization. Priority research domains include digital health systems, AI-enabled triage, and physiological analytics.
NOAA Small Business Innovation Research (SBIR) Program FY 2025 Phase I is sponsored by National Oceanic and Atmospheric Administration (NOAA). The NOAA SBIR Program encourages proposals from qualified small businesses for highly innovative technologies with strong commercial potential that fit within NOAA's mission areas, including Artificial Intelligence. Phase I awards fund a six-month period for feasibility and proof of concept research.
Innovative Research in Cancer Nanotechnology (IRCN; R01 Clinical Trial Not Allowed) is sponsored by National Cancer Institute (NCI). This NOFO encourages applications promoting transformative discoveries in cancer biology and/or oncology through the use of nanotechnology. It specifically mentions the integration of modeling and simulation approaches to guide rational nanomaterial design and the use of artificial intelligence (AI) and modeling to aid rational drug design. This directly relates to personalized medicine and cancer treatment, though the primary focus is nanotechnology.
The Department of Defense FY2026 Defense University Research Instrumentation Program (DURIP) provides funding for U.S. universities to acquire research equipment and instrumentation in areas important to national defense, including AI and machine learning hardware. The program is administered jointly by the Army Research Office (ARO), Office of Naval Research (ONR), and Air Force Office of Scientific Research (AFOSR), with approximately $34 million available and 95 awards anticipated. DURIP funds the acquisition of specialized computing hardware for AI/ML research (GPU clusters, TPUs, neuromorphic processors), robotics and autonomous systems testbeds, sensor arrays and data collection systems for machine learning training, high-performance computing infrastructure for defense-relevant AI research, and laboratory equipment for human-AI interaction studies. The program specifically supports equipment that enhances research-related education in DoD-priority disciplines. While general-purpose computing is not eligible, computing equipment directly supporting DoD-relevant AI research programs qualifies. No cost sharing is required.
NIST Small Business Innovation Research (SBIR) Phase II Program - Quantum Information Science is sponsored by National Institute of Standards and Technology (NIST). This program allocates funding to small businesses for prototyping innovative technologies in areas including quantum information science, artificial intelligence, and semiconductors. These Phase II awards follow successful Phase I feasibility studies.
Broad Agency Announcement (BAA) Call N0001425SBC03 For Office of Naval Research (ONR) Global Opportunity: GlobalX Innovation Joint Challenge: AI for Advancing Maritime Security is sponsored by Office of Naval Research (ONR) Global. This BAA Call seeks proposals for the GlobalX Innovation Joint Challenge: AI for Advancing Maritime Security. It funds the development of artificial intelligence solutions for maritime security applications, focusing on innovative AI algorithms for challenging maritime scene perception scenarios using real-world or synthetic data from UxV platforms. The program aims to accelerate the traditional knowledge generation cycle, leading to revolutionary dual-use capability for the U.S. Navy and Marine Corps and the commercial marketplace. White papers are highly encouraged and due May 23, 2025, with full proposals due June 23, 2025.
Agriculture and Food Research Initiative (AFRI) Foundational and Applied Science Request for Applications (AI components) is sponsored by U.S. Department of Agriculture (USDA), National Institute of Food and Agriculture (NIFA). The subsections of the AFRI Foundational and Applied Science program that provide funding in AI are Agriculture Systems and Technology; Bioenergy, Natural Resources and Environment; and Agricultural Economics and Rural Community program areas.
Agriculture and Food Research Initiative (AFRI) Foundational and Applied Science Request for Applications (AI components) is sponsored by USDA National Institute of Food and Agriculture (NIFA). This program supports AI activities that advance the ability of computer systems to perform tasks traditionally requiring human intelligence within agriculture and the food supply chain. This includes machine learning, data visualization, natural language processing, intelligent decision support systems, and autonomous systems for agricultural and food production.
Smart Health and Biomedical Research in the Era of Artificial Intelligence and Advanced Data Science (SCH) is sponsored by National Science Foundation (NSF) / National Institutes of Health (NIH). This interagency program supports transformative, high-risk/high-reward advances in computer and information science, engineering, mathematics, statistics, behavioral, and cognitive research to address pressing questions in biomedical and public health. It focuses on interdisciplinary teams developing novel methods to intelligently collect, sense, connect, analyze, and interpret data from individuals, devices, and systems to enable discovery and optimize health. This includes effective data generation, analysis, and automation for biomedical devices, systems (e.g., electronic health records), and consumer devices.
Smart Health and Biomedical Research in the Era of Artificial Intelligence and Advanced Data Science (SCH) is sponsored by National Science Foundation (NSF) & National Institutes of Health (NIH). This program encourages proposals at the intersection of computer and information science and engineering, and the biological, behavioral, clinical, and social sciences to develop and apply intelligent systems for health and biomedical research. Research focusing on AI-driven approaches for understanding, preventing, or treating diabetes complications, including eye disease, would be relevant.
Smart Health and Biomedical Research in the Era of AI and Advanced Data Science (SCH) is sponsored by National Science Foundation (NSF) and National Institutes of Health (NIH). This joint NSF/NIH program supports high-risk, high-reward interdisciplinary projects that utilize artificial intelligence, advanced data science, and engineering to solve pressing challenges in healthcare and public health. Projects must cross disciplinary boundaries, with teams pairing computer scientists with clinicians or public health researchers being an explicit target. Dental AI software could fit within the scope of advanced data science and AI applications in healthcare.
AI Compute Access Fund is sponsored by Innovation, Science and Economic Development Canada (ISED). The AI Compute Access Fund is a national initiative to help Canadian innovators and businesses (SMEs) access high-performance computing resources. It aims to accelerate the development and deployment of made-in-Canada AI solutions by offsetting the high cost of compute resources, particularly in sectors requiring significant computing capacity like life sciences, energy, and advanced manufacturing.
2025 Faculty Scholars Grant Program is a grant from the Foundation for Academic Nursing that funds nursing faculty scholarship projects at AACN member schools. The program distributes a total of $50,000 to support two $25,000 projects through the 2025-2026 academic year, focusing on two themes: integrating health policy into the nursing curriculum and using artificial intelligence in nursing education. Projects are expected to measure the impact of didactic and clinical learning experiences on these themes at graduate and undergraduate levels. All faculty at AACN member schools are eligible to apply. The 2025 application deadline was August 8, 2025, with recipients notified in early November.
Expanding K-12 Resources For AI Education is sponsored by U.S. National Science Foundation (NSF). This Dear Colleague Letter (DCL) invites supplemental funding proposals from existing NSF awardees with K-12 AI or computer science education experience. The aim is to refine, scale, evaluate, and/or implement established K-12 activities related to AI education. Proposed efforts should align with themes such as teacher professional development, curricula and instructional materials, and technology and tools for AI education.
NSF STEM K-12 (STEM K-12) is sponsored by National Science Foundation (NSF). This program supports fundamental, applied, and translational research that advances STEM teaching and learning and improves understanding of education across the human lifespan and in a range of formal and informal settings. It encourages innovative, multidisciplinary projects leveraging AI and emerging technologies to strengthen U.S. STEM education and workforce.
National Artificial Intelligence Research Resource (NAIRR) Pilot is sponsored by U.S. National Science Foundation (NSF). The NAIRR Pilot is a public-private initiative connecting U.S. researchers and educators to advanced computational and data platforms, datasets, software, AI models, and technological expertise to accelerate AI-driven discovery and innovation. While broad in scope, research into trustworthy AI, human-AI interaction, and the societal implications of AI (including in sectors like hospitality and tourism) would be relevant.
The FY2026 Department of Defense Multidisciplinary University Research Initiative (MURI) program supports basic research in science and engineering at U.S. institutions of higher education, with emphasis on multidisciplinary research where more than one traditional discipline interacts. The Army, Navy, and Air Force basic research offices are seeking applications across 22 topic areas including artificial intelligence and autonomy, information sensing and processing, and systems manipulation. MURI grants typically provide $1.25 million to $1.5 million per year for three years with option to extend two additional years. Approximately $170 million in total funding is available annually across all topics. The program is administered through the Office of Naval Research (ONR), Army Research Office (ARO), and Air Force Office of Scientific Research (AFOSR).
Innovate UK's Sovereign AI Proof of Concept programme funds proof of concept demonstrators of AI technologies with state-of-the-art performance across five strategic themes: fundamental AI research, materials discovery, biosciences and health, defense and national security, and AI-aided chip/hardware design. Individual project grants range from £50,000 to £120,000 (approximately USD $63,500-$152,400) from a total allocation of at least £1.6 million. Projects must be 1-3 months in duration, starting by January 2026 and completing by March 2026. The programme supports feasibility studies and industrial research, with funding covering up to 70% of costs for micro/small businesses, 60% for medium, and 50% for large organizations. Literature review studies and projects unable to scale are excluded.
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.
2025-2026 FRC Sponsorship Grants is a grant program from NASA's Robotics Alliance Project that funds rookie and second-year FIRST Robotics Competition (FRC) teams to cover registration and equipment costs, enabling students to participate in the FRC competition season. NASA's support provides students with hands-on engineering challenges, transforming ideas into functioning robots while developing critical STEM skills, teamwork, and problem-solving abilities. Grants cover registration fees and are targeted at teams in their first two years of competition who meet specific NASA eligibility criteria. Eligible applicants are first-year (rookie) and second-year FRC teams meeting program requirements. Award amounts vary based on team needs and program guidelines. Teams should apply through NASA's FRC grant application portal and submit early as processing is competitive.
AI for Economic Opportunity Fund is sponsored by GitLab Foundation, in partnership with OpenAI. This fund awards demonstration grants to US-based nonprofits using AI to measurably improve economic mobility for low-income populations. Priority areas include AI solutions that unlock siloed data, expand agent interoperability, reduce service delivery costs, personalize learning, validate skills, and strengthen labor market intelligence. Selected organizations also receive technical support from OpenAI engineers and API credits.
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 purpose of this RFI is to solicit feedback from industry, academia, research laboratories, government agencies, impacted communities and other stakeholders on issues related to gigawatt-scale generation and transmission investments driven by projected electricity demand growth from data centers, advanced manufacturing facilities, semiconductor fabrication plants, and other large energy users that are outpacing the capacity of the existing electric grid. Funding Opportunity Number: DE-FOA-0003574. Assistance Listing: 81.254. Funding Instrument: G. Category: EN. Award Amount: $1 – $2 per award.
Vinnova, Sweden's national innovation agency, funds projects developing applied AI solutions for Swedish industry through its Advanced Digitalization Programme. Each project can apply for between 2 and 10 million SEK (approximately $190,000 to $950,000 USD) covering up to 50% of eligible project costs. The total call budget is 60 million SEK. Projects run for 12-24 months and focus on two key areas: Intelligent Edge (AI for real-time application in the sensor chain) and AI-based decision support. All projects must address industrial needs and integrate gender equality and climate change perspectives. Scientific publications must be open access. A parallel call also funds AI and cybersecurity projects at 1-10 million SEK per project with a 50 million SEK total budget.
Coefficient Giving Request for Proposals: AI Governance is a grant opportunity from Coefficient Giving that funds research and projects aimed at reducing catastrophic risks from advanced artificial intelligence. The program supports work across six subject areas: technical AI governance, policy development, frontier company policy, international AI governance, law, and strategic analysis and threat modeling. Strong proposals address scenarios where AI could cause large-scale harm — including misuse by bad actors or loss of control over autonomous systems. Eligible applicants include individuals and organizations from academia, nonprofits, industry, or independent settings worldwide. Award amounts are not publicly specified but grants are evaluated on a rolling basis and may be co-funded by Good Ventures and over 20 additional philanthropists. The January 25, 2026 deadline has passed; future rounds are anticipated.
Hoffman-Yee Grant is a grant from Stanford Institute for Human-Centered Artificial Intelligence (HAI) that funds interdisciplinary research teams at Stanford University advancing human-centered AI across three focus areas: developing novel intelligence technologies, designing AI that augments rather than replaces humans, and understanding and guiding the societal impact of AI. Proposals must address significant scientific, technical, or societal challenges requiring interdisciplinary collaboration. Letters of Intent were due January 28, 2026. The 2026 cycle particularly invites proposals leveraging AI to drive advances in scientific discovery. Eligible applicants are Stanford faculty-led interdisciplinary teams.
The IAPS AI Policy Fellowship is a fully funded three-month program for professionals seeking to strengthen practical policy skills and contribute to impactful projects in AI governance and policy. The Summer 2026 cohort runs from June to August 2026 with options to participate in Washington DC or remotely. The program begins with a two-week in-person residency in Washington DC followed by remote or in-person work with weekly mentorship and career development support. Fellows work full-time on independent AI policy projects covering areas such as AI regulation compute governance international AI agreements AI safety policy AI workforce impacts and responsible AI deployment. The fellowship received 240 applications for the 2026 cohort representing a 35 percent increase over 2025. IAPS is a remote-first organization and legally supports fellows in many countries. This fellowship is distinct from the Vista Institute for AI Policy Fellowship which focuses specifically on AI law and from the Cooperative AI Foundation fellowships which focus on multi-agent cooperation problems.
The NSF Collaborations in Artificial Intelligence and Geosciences (CAIG) program (NSF 25-530) funds interdisciplinary research teams that advance Earth system science through innovative AI methods. Jointly managed by NSF's Directorate for Geosciences (GEO/RISE), Division of Information and Intelligent Systems (CISE/IIS), Office of Advanced Cyberinfrastructure (CISE/OAC), and Division of Mathematical Sciences (MPS/DMS), the program supports projects that push the boundaries of both geoscience and AI. Each competition allocates $6 million to $10 million across 5-9 awards for projects lasting up to 3 years. Funded projects must demonstrate three core objectives: advancing geoscience research through AI, making impactful advancements in AI methodologies applicable to geosciences, and forming meaningful interdisciplinary partnerships involving diverse teams of 2-3 lead senior/key personnel. The solicitation covers both a 2025 and 2026 competition, with the 2026 full proposal deadline of February 4, 2026. The program supports work in climate modeling, weather prediction, ocean science, atmospheric science, and other geoscience domains where AI can enable significant breakthroughs. Future competition cycles are anticipated under subsequent solicitations.
The Kavli Foundation sponsors an AI-for-Science Postdoctoral Fellowship through FutureHouse's Independent Postdoctoral Fellowship program, supporting one fellow per cohort to pursue an independent, AI-enabled research project in neuroscience. The fellowship provides a $125,000 annual stipend plus comprehensive benefits, travel allowance for conferences, dedicated software engineering support for building AI research tools, access to advanced computational resources (GPU clusters and cloud computing), and wet lab access for experimental validation. Fellows work in collaboration with an advisor or co-advisor who is a member of a Kavli Institute, pursuing bold, curiosity-driven projects in neuroscience ranging from molecular and cellular mechanisms to systems-level understanding of the brain. The fellowship begins September 2026 and runs for one year with a possible one-year extension. Research areas include AI-driven analysis of brain imaging data, machine learning for neural circuit mapping, computational neuroscience models, AI tools for analyzing large-scale neural recordings, and deep learning applied to connectomics and brain-computer interfaces.
Ruth L. Kirschstein Individual Postdoctoral Fellowship (F32) is sponsored by National Eye Institute (NEI). This fellowship supports promising postdoctoral researchers who are committed to a career in health-related research. The NEI encourages applications from individuals with backgrounds in neuroscience, data science, computer science, artificial intelligence, engineering, and epidemiology to further NEI's mission in biology and diseases of the eye.
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