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NSF 26-513 establishes State and Regional AI Infrastructure Hubs to widen access to AI compute for scientific discovery, with approximately 100,000,000 dollars available and about 10 awards anticipated per cycle at 4,000,000 to 12,000,000 dollars each over five years.
A hub coordinates a state or multi-state consortium and funds three things that are usually unfunded in AI infrastructure efforts: AI infrastructure professionals such as systems administrators, engineers and cybersecurity specialists; AI-for-science facilitators who advise domain researchers on how to actually use AI methods; and faculty training plus instructional material development.
It also funds workforce development offering stackable credentials in data engineering, research software engineering and GPU programming. The structural signal in this solicitation is that NSF has concluded the bottleneck in AI-enabled research is human rather than hardware, and is paying for the expertise layer between a researcher and a cluster.
The restriction of one award per state or multi-state region makes this a coordination instrument rather than an open competition: institutions within a region are expected to consolidate into a single proposal, which means partnership-building should begin well before the submission window. Deadlines recur on the first Wednesday in November annually, with the current deadline 4 November 2026 followed by 3 November 2027.
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Or search similar grants →According to the current listing, eligibility includes: Eligible proposers are U.S. institutions of higher education, including both two-year and four-year institutions and explicitly community colleges, and non-profit non-academic organizations. The limits are strict and shape strategy more than the scope statement does: one proposal per institution, each individual may serve as PI or co-PI on only one proposal per deadline, and critically only one award will be made per state or multi-state region. That last rule means an institution's real decision is whether to lead a regional consortium or join one, because two competing proposals from the same state cannot both be funded. The inclusion of community colleges as eligible lead organizations is deliberate and distinguishes this from most NSF AI infrastructure funding, as does the eligibility of non-profit non-academic organizations, which opens the door to regional consortia anchored by non-university entities. Proposals are expected to cover consortium coordination, hiring of AI infrastructure professionals and AI-for-science facilitators, faculty training and instructional materials, and workforce development with stackable credentials in data engineering, research software engineering and GPU programming. The five-year duration means staffing plans must be sustainable across the full period, and the annual recurring deadline means an unsuccessful regional consortium can resubmit, but only if no other proposal from that region has been funded in the interim. Proposals are due 4 November 2026. Confirm the full requirements in the official notice before applying.
The current listing shows awards range from a minimum of 4,000,000 US dollars to a maximum of 12,000,000 US dollars per hub, against a program total of approximately 100,000,000 dollars, with roughly 10 awards anticipated in each annual cycle and a five-year performance period. The arithmetic is the first thing to check against ambition: 100 million dollars divided across about 10 awards implies an average near 10 million, so the 12 million ceiling is close to the expected award rather than an outlier reserved for exceptional proposals, and a 4 million floor signals that NSF will fund smaller single-state consortia as well as large multi-state ones. Spread over five years, a 12 million dollar hub is roughly 2.4 million dollars per year, which is enough to staff a team of AI infrastructure professionals and AI-for-science facilitators but is not capital funding for a GPU cluster. That distinction is the most common misreading of this solicitation: the money buys people, training and coordination that expand access to existing compute, not the compute itself. The one-award-per-state-or-multi-state-region rule also means the real competition is intra-regional rather than national, so the binding constraint on budget size is usually what the regional consortium can justify, not what NSF will entertain. Verify award ceilings, matching requirements, and allowable costs in the official notice.
Applications for NSF State and Regional Artificial Intelligence Infrastructure Hubs (NSF 26-513) for Expanding Access to AI Compute, AI-for-Science Facilitation and AI Workforce Credentials are due November 4, 2026. Build your timeline backwards from this date to cover registrations, approvals, and final submission checks.
NSF State and Regional Artificial Intelligence Infrastructure Hubs (NSF 26-513) for Expanding Access to AI Compute, AI-for-Science Facilitation and AI Workforce Credentials is funded by U.S. National Science Foundation (NSF). 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 ONR Long Range Broad Agency Announcement (N00014-25-S-B001) is the Office of Naval Research's primary mechanism for soliciting research proposals across all naval science and technology priority areas. The BAA accepts proposals on a rolling basis through September 30, 2026 and covers ONR's full spectrum of research interests with particular emphasis on AI-related topics including autonomous maritime systems, human-machine teaming, machine learning for sensor fusion, cooperative autonomous swarm technology, undersea autonomy, and AI-enabled decision superiority. Proposals can be funded through multiple mechanisms including individual investigator grants, the Young Investigator Program (~$510K over 3 years for early-career faculty), and Multidisciplinary University Research Initiative (MURI) awards ($1.5M/year for 3-5 years for research teams). ONR recommends contacting relevant program officers before submitting to discuss alignment with current research priorities. The BAA supports basic research (6.1), applied research (6.2), and advanced technology development (6.3) across the full range of naval-relevant science and engineering disciplines.
PRIMED-AI is a new NIH Common Fund programme, Precision Medicine with AI: Integrating Imaging with Multimodal Data, which combines medical imaging with other health data to build AI-powered clinical decision support tools for personalised medicine. This opportunity, RFA-RM-27-014, funds the programme's Validation Center: a dedicated hub that independently evaluates and characterises the AI-enabled, image-based multimodal clinical decision support tools developed elsewhere in the consortium. The structural logic matters for applicants. NIH has separated tool-building from tool-validation and is paying separately for the second, which signals institutional recognition that self-reported performance claims from developing teams are not sufficient evidence for clinical AI. The Center's remit covers verification, validation, interoperability and uncertainty quantification, so the deliverable is a reproducible evaluation capability rather than a set of papers. It operates as a U54 cooperative agreement, meaning NIH staff are substantively involved and the Center must work in concert with the PRIMED-AI Logistics Center and the Data-to-Model and Model-to-Clinic award recipients. The RFA was released on 30 June 2026 with applications due 2 October 2026. For academic groups that have built credible AI evaluation methodology, particularly in radiology, imaging informatics or biostatistics, this is an unusually direct route to becoming the reference evaluator for a major federal AI health programme, and the position carries influence over how clinical AI performance gets measured well beyond the life of the award.
RFA-RM-27-015 funds a single Logistics Center as the coordinating hub of the NIH Common Fund's PRIMED-AI program, Precision Medicine with AI: Integrating Imaging with Multimodal Data. The award is a cooperative agreement, meaning substantial NIH scientific and programmatic involvement is built in rather than incidental, and it is administered by NIBIB on behalf of the Common Fund. The Center operates through three integrated cores: Administration, which runs the steering committees and develops consortium policies; Evaluation, which assesses progress across the funded portfolio; and Outreach, which maintains a web portal for sharing AI-based clinical decision support tools and facilitates engagement between researchers, clinicians and patient communities. The strategic point for applicants is that this is the only coordinating award in a multi-award program whose other components, the Data-to-Model Academic-Industrial Partnerships, Model-to-Clinic and Multi-use Frameworks Playbook RFAs, are separately competed and separately funded. The Logistics Center therefore does not generate its own AI models; it is scored on its capacity to run a consortium, set data and tool-sharing policy, and build infrastructure that makes other teams' clinical decision support tools discoverable and reusable. Applications are due by 5:00 PM local time of the applicant organization on the date specified for the relevant review cycle, with an earliest project start date of 2 October 2026 and a maximum project period of five years.
NSF obligated $6.4 billion across 6,218 awards in FY2026, down from $8.3 billion and 8,647. An August OMB apportionment carried $1.7 billion into FY2027, roughly $1 billion of it reserved for the White House Grand Research Challenges initiative. NIH, by contrast, spent its full $34 billion. Here is what the carryover mechanism actually means for your FY2027 proposal — and why the directorate you submit to now matters more than the score you get.
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