1,000+ Opportunities
Find the right grant
Search federal, foundation, and corporate grants with AI — or browse by agency, topic, and state.
NIH Bridge2AI Stage 2 represents the next phase of the NIH Common Fund Bridge to Artificial Intelligence program building on $130 million invested in Stage 1 to create ethically sourced AI-ready biomedical datasets. Stage 2 shifts focus from data generation to building tools devices and safety frameworks that translate those datasets into clinical and research applications.
Two interconnected initiatives are funded: Innovation Funnels supporting teams that use Stage 1 AI-ready datasets to create practical tools including diagnostic algorithms drug discovery platforms and clinical decision support systems that demonstrate measurable health impact and a Network for AI Health Science developing safety measures validation protocols and responsible-use frameworks for AI in health research.
The program values interdisciplinary teams combining computational scientists with domain experts in specific disease areas. Stage 2 Requests for Applications are expected by mid-2026. This is distinct from ARPA-H programs which fund specific high-risk clinical AI applications and from AHRQ healthcare AI safety grants which examine existing AI impact on healthcare systems.
Get a weekly digest of new grants like this
A free weekly digest of new foundation and federal funding opportunities as they're added to Granted. Unsubscribe anytime.
Or search similar grants →According to the current listing, eligibility includes: Researchers with expertise in both AI/ML methods and specific disease areas at US institutions of higher education research institutes and eligible nonprofits. Bridge2AI explicitly values interdisciplinary teams. Stage 2 RFAs have not yet been posted but are expected by mid-2026. Monitor commonfund.nih.gov/bridge2ai/funding for announcements. Confirm the full requirements in the official notice before applying.
The current listing shows $130 million over four years for Stage 2 pending availability of funds. Stage 1 invested $130 million to create ethically sourced AI-ready datasets. Stage 2 will fund Innovation Funnels translating those datasets into clinical tools and a Network for AI Health Science developing safety and validation protocols. Individual award amounts will be specified in forthcoming RFAs. Verify award ceilings, matching requirements, and allowable costs in the official notice.
NIH Bridge2AI Stage 2 Innovation Funnels and Network for AI Health Science is funded by National Institutes of Health Common Fund. Verify program details on the funder's official page before applying.
Yes — this listing is flagged as national in scope, so applicants across the U.S. may apply, subject to the sponsor's other eligibility criteria.
Applications go through the funder's official portal — the Apply Now link on this page goes there directly.
Development and Testing of a Multi-use Frameworks Playbook for Precision Medicine with AI: Integrating Imaging with Multimodal Data (PRIMED-AI) (U01 Clinical Trial Not Allowed) is sponsored by National Institutes of Health Common Fund. This opportunity solicits applications for the design, development, and preliminary validation of robust frameworks for the application of multimodal-artificial intelligence (AI) models for clinical use. The frameworks are expected to address PRIMED-AI objectives and needs while remaining flexible and interoperable for a broad spectrum of multimodal biomedical AI applications.
Model-to-Clinic (M2C) for Precision Medicine with AI: Integrating Imaging with Multimodal Data (PRIMED-AI) (UG3/UH3, Clinical Trial Optional) is sponsored by National Institutes of Health Common Fund. This opportunity catalyzes the translation of AI-enabled, image-centered, multimodal Clinical Decision Support (CDS) tools, developed as Software as a Medical Device (SaMD), from validated prototypes to clinical applications addressing unmet precision medicine challenges. Projects are expected to have a high potential for demonstrable, positive impact on patient outcomes and/or healthcare processes.
The NEH Humanities Research Centers on Artificial Intelligence program funds the creation of university-based humanities research centers focused on the ethical, legal, and societal implications of artificial intelligence. Funded centers undertake interdisciplinary humanities-led research that brings ethics, law, history, philosophy, anthropology, religious studies, literature, linguistics, and cultural studies to bear on questions raised by AI systems. Topics include responsible AI governance frameworks, AI and civil rights, AI and labor, cultural impact of generative AI, AI and creative authorship, philosophical foundations of machine reasoning, history of AI thought, and humanistic evaluation of AI safety and alignment. Centers are expected to convene researchers, train new humanities scholars in AI, host public-facing programming, and produce publications and translational tools that inform policy and public understanding. Strong fit for universities seeking to launch sustained interdisciplinary AI humanities research programs in partnership with computer science and other STEM departments.
NSF SaTC 2.0 (Security Privacy and Trust in Cyberspace) is the largest open solicitation for university-led cybersecurity research in the federal portfolio now expanded with AI security as an explicit priority area. The 2.0 reboot added generative AI security open-source software security quantum computing security and supply chain security as topics of interest addressing the bidirectional role of AI as both a cybersecurity threat and a defensive tool. Research awards support adversarial machine learning and attacks on AI systems AI weaponization against people information and systems privacy-preserving machine learning and responsible AI use for detecting and responding to cyber threats. The program funds three award types: Research awards up to $1.2M for four years Education awards up to $500K for three years and Seedling awards up to $300K for two years through Dear Colleague Letters. Proposals are accepted on a recurring annual basis with two windows per year. This is distinct from NSF CyberAICorps which focuses on scholarship and workforce development and from NSF AIMing which focuses on AI formal methods and mathematical reasoning.
The Air Force Research Laboratory Information Directorate's Geospatial Intelligence Processing and Exploitation (GeoPEX) Broad Agency Announcement, FA8750-21-S-7006, is an open two-step BAA soliciting white papers for research, development, integration, test, and evaluation of technologies and techniques to provide geospatial intelligence (GEOINT) in all its forms and from whatever source, including imagery, imagery intelligence, and geospatial data. Explicit focus areas include AI/ML techniques for full-spectrum GEOINT, multi-INT data fusion, cloud-based high-performance computing for geospatial analytics, photogrammetry, computer vision for overhead imagery, automated target recognition, change detection, multi-modal foundation models for geospatial data, and edge AI for tactical reconnaissance. The BAA is open and effective until 30 September 2026 with rolling white paper submission; only white papers are accepted as initial submissions and formal proposals are accepted by invitation only. Strong fit for AI and computer vision performers building geospatial analytics, foundation models, or autonomous reconnaissance tools for Air Force, intelligence community, and combatant command users.
NOT-RM-26-004 asks the public for NIH-wide research challenges worth a 10-year, cross-institute program. There is no budget, no biosketch, no page limit, and no award. What there is: the five criteria every Common Fund investment has met since 2006, a new bullet about small-lab burden, and a fund whose FY 2026 request came in at $347.4 million — down 49.3 percent.
Read articleThe NIH Common Fund launched PRIMED-AI — Precision Medicine with AI: Integrating Imaging with Multimodal Data — as five coordinated funding opportunities (RFA-RM-27-011 through -015) that build a full pipeline from standards to clinic. Here is how the Playbook, Data-to-Model partnerships, Model-to-Clinic translation, Validation Center, and Logistics Center fit together, what each pays, who is eligible, and how to position before the October 2026 deadlines.
Read articleAvoid common NIH grant proposal mistakes including vague specific aims, weak methodology, and poor budget justification that lead to rejection.
Read article