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NSF 24-561 recurs annually with full proposal deadline first Monday in May; next cycle May 3, 2027
The Foundations for Digital Twins as Catalyzers of Biomedical Technological Innovation (FDT-BioTech) program is a tri-agency initiative by NSF, NIH, and FDA supporting inherently interdisciplinary research that underpins the mathematical and engineering foundations behind the development and use of digital twins and synthetic data in biomedical and healthcare applications.
The program funds advances in mathematics, statistics, computational sciences, and engineering required to develop responsive digital twin models incorporating artificial intelligence capabilities. Research areas include in silico models for medical device evaluation, synthetic human generation, and emerging challenges in biomedical technology development and assessment.
Awards are up to $1,000,000 for collaborative projects from multiple organizations over 3 years, with the program issuing 6 to 10 awards per cycle. The next deadline is May 4, 2026, with annual cycles on the first Monday of May thereafter. This program specifically targets the foundational computational methods that make biomedical digital twins possible rather than application-specific implementations.
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Or search similar grants →According to the current listing, eligibility includes: Interdisciplinary research teams at institutions eligible to receive NSF funding. Each individual may serve as PI or co-PI on no more than one proposal. Collaborative projects from multiple organizations encouraged. Standard NSF eligibility requirements apply including U.S. academic institutions and nonprofits. Confirm the full requirements in the official notice before applying.
The current listing shows up to $1,000,000 per collaborative project over 3 years. Total program funding estimated at $4,000,000 to $5,000,000 per fiscal year. Approximately 6 to 10 awards expected. Verify award ceilings, matching requirements, and allowable costs in the official notice.
Applications for NSF FDT-BioTech Foundations for Digital Twins as Catalyzers of Biomedical Technological Innovation are due May 3, 2027. This is an annual program. Build your timeline backwards from this date to cover registrations, approvals, and final submission checks.
NSF FDT-BioTech Foundations for Digital Twins as Catalyzers of Biomedical Technological Innovation is funded by National Science Foundation with NIH and FDA. 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.
Start from the official opportunity page linked in this listing — it carries the sponsor's submission instructions.
NSF FDT-BioTech Foundations for Digital Twins as Catalyzers of Biomedical Technological Innovation is sponsored by National Science Foundation with NIH and FDA. The Foundations for Digital Twins as Catalyzers of Biomedical Technological Innovation (FDT-BioTech) program is a tri-agency initiative by NSF, NIH, and FDA supporting inherently interdisciplinary research that underpins the mathematical and engineering foundations behind the de…
The FDT-BioTech program is a joint NSF NIH and FDA initiative that catalyzes biomedical technological innovation through foundational development of methods and algorithms relevant to digital twins and synthetic humans. The program supports inherently interdisciplinary research projects that underpin the mathematical and engineering foundations behind the development and use of digital twins and synthetic data in biomedical and healthcare applications with a particular focus on digital in silico models used in the evaluation of medical devices and to advance regulatory sciences. Priority research areas include computational representations of physiological systems verification validation and uncertainty quantification transferability and generalizability across populations ethics security and privacy considerations and validation mechanisms for digital twin models. The program incorporates AI and machine learning as key enabling technologies for creating responsive digital twin models. All proposals must address regulatory science benefits and ethical implications. This program is distinct from the NSF SCH Smart Health program which focuses broadly on AI for health research and from ARPA-H programs which target specific clinical applications.
The NSF Computer and Information Science and Engineering: Future Computing Research (Future CoRe) program (NSF 25-543) supports foundational computing research and education with a strong emphasis on AI and machine learning. The program funds research that advances the foundations of computing including AI/ML theory, algorithms, systems, and applications. Future CoRe supports small to medium-sized research projects that can have significant impact on computing foundations. The program has target dates of February 5, 2026 and September 10, 2026 for proposal submissions (note: these are target dates, not deadlines, meaning proposals may be submitted at any time but will be reviewed in batches around these dates). Investigators may not serve as PI, co-PI, or Senior/Key Personnel on more than two proposals submitted within any consecutive 12-month period across all Future CoRe programs. This is one of NSF's primary mechanisms for funding fundamental AI and machine learning research at U.S. academic institutions, covering areas such as machine learning theory, natural language processing, computer vision, robotics foundations, and human-AI interaction.
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.
DE-FOA-0003600 is the DOE Office of Science's FY 2026 open, rolling solicitation for financial assistance, providing roughly $500 million across seven program areas: Advanced Scientific Computing Research, Basic Energy Sciences, Biological and Environmental Research, Fusion Energy Sciences, High Energy Physics, Nuclear Physics, and Isotope R&D and Production. AI and machine learning research is supported directly through Advanced Scientific Computing Research, while Biological and Environmental Research funds atmospheric process research, environmental systems process research, and earth-energy systems modeling — making this a major channel for AI-enhanced climate and earth system modeling work. DOE anticipates 200 to 350 new awards ranging from $5,000 to $5 million each, with project periods from six months to five years. The FOA opened September 30, 2025 and accepts applications on a rolling basis through the end of FY 2026.
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