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NSF 26-513 establishes State and Regional Artificial Intelligence Infrastructure Hubs to expand researcher access to AI computing, with approximately 100 million US dollars available and about 10 awards anticipated per cycle, one per state or multi-state region, at 4 to 12 million dollars each.
The solicitation addresses five core elements: hub consortium governance built on multi-institutional partnerships spanning higher education, industry, philanthropy and state and local government; computing, data, software and other AI infrastructure, funded by the consortia rather than by NSF; regional partnerships including industry collaboration, workforce development and integration with the National AI Research Resource; an AI infrastructure workforce of systems administrators, engineers and AI for science facilitators who support researcher access; and faculty training through instructional materials, labs, workshops and programmes that help students use computing and data resources for scientific research.
The diagnosis behind the programme is that the constraint on AI-enabled science at most United States institutions is no longer the existence of compute but the absence of local capacity to make it usable: no facilitators, no trained faculty, no institutional pathway to a national resource.
The solicitation is domain-neutral, emphasising broad enablement across science and engineering rather than naming healthcare, climate or agriculture priorities, which means a hub serving an agricultural or biomedical research region can shape its proposal around that regional strength without working against the call. Full proposals are due 4 November 2026, then 3 November 2027 and the first Wednesday in November annually thereafter.
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Or search similar grants →According to the current listing, eligibility includes: Proposals may be submitted by two- and four-year institutions of higher education, including community colleges, that are accredited in and have a campus located in the United States, and by United States-based non-profit non-academic research organisations. The limits are strict: one proposal per institution and one proposal per individual as principal investigator or co-principal investigator, which forces internal coordination at any institution where multiple groups might wish to lead and makes early institutional alignment essential. The de facto eligibility requirement beyond these formal rules is the consortium. Because NSF does not fund the computing infrastructure itself, a competitive application must arrive with a governance structure and documented commitments from consortium members, potentially including other higher education institutions, industry, philanthropy and state or local government, that supply the compute, data and software capacity the hub will make accessible. One award is anticipated per state or multi-state region, so applicants should establish early whether another institution in their state is also preparing a proposal; a fragmented state is a weaker candidate than a coordinated one, and the one-proposal-per-institution rule combined with the one-award-per-region expectation strongly favours a single consolidated regional bid. Applicants should also plan for integration with the National AI Research Resource and should budget for AI infrastructure workforce roles and faculty and student training, which are explicit programme elements rather than optional additions. Full proposals are due 4 November 2026 and 3 November 2027, recurring the first Wednesday in November annually. Confirm the full requirements in the official notice before applying.
The current listing shows individual awards carry a total budget range of 4,000,000 to 12,000,000 US dollars, so amount_min is recorded as 4,000,000 and amount_max as 12,000,000 US dollars. Approximately 100,000,000 US dollars is available in total, with 10 awards anticipated per cycle, one per state or multi-state region. The most important financial fact about this solicitation is what the money does not pay for: the computing, data, software and other AI infrastructure itself is expected to be funded by the hub consortium rather than by NSF. NSF money pays for governance, coordination, the AI infrastructure workforce and faculty and student training, and applicants who budget as though NSF will buy the cluster have misread the solicitation. In practice this makes the award a matching-and-coordination instrument: the credible application arrives with documented commitments of compute and capital from consortium members, which may include industry, philanthropy and state or local government, and uses NSF funds to make that capacity usable by researchers who currently cannot access it. The workforce element is where a large share of the budget realistically goes, covering systems administrators, engineers and AI for science facilitators who support researcher access, and this is one of the few federal mechanisms that will fund research-facilitation staff as a primary deliverable rather than as institutional overhead. Over a five-year project period the 4 to 12 million dollar range translates to roughly 0.8 to 2.4 million dollars per year, which is a coordination-scale budget rather than a facility-scale one. 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) Expanding Access to Compute for Scientific Discovery 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) Expanding Access to Compute for Scientific Discovery is funded by U.S. National Science Foundation (NSF), Directorates for Computer and Information Science and Engineering (CISE), STEM Education (EDU) and Technology, Innovation and Partnerships (TIP). 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.
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