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PAR-26-040 is the National Library of Medicine's standing R01 vehicle for bioinformatics, translational bioinformatics and computational biology, and it is one of the more accessible NIH entry points for AI and machine learning work on biomedical data.
The NOFO explicitly names artificial intelligence, machine learning and large-scale computational platforms among the transformative technologies it seeks to leverage for extracting actionable knowledge from vast, diverse and complex biological datasets, and it calls out studies that use AI and ML applications for predictive and analytical bioinformatics research as being in scope.
That explicit language is worth noting, because AI-heavy proposals submitted to general biomedical NOFOs frequently draw reviewer objections that the methods work is not the point of the call; here it is. Three structural features make this an unusually practical target.
First, it is a parent-style PAR with multiple rolling due dates running from 5 June 2026 through 5 February 2029 and an expiration of 6 March 2029, so there is no single make-or-break deadline and a resubmission has somewhere to go.
Second, eligibility is broad - higher education institutions, nonprofits, for-profits including small businesses, state, local, federal and tribal governments, and foreign entities are all eligible, and cost sharing is not required. Foreign institution eligibility in particular is not universal across NIH NOFOs and is a genuine differentiator.
Third, clinical trials are optional and human subjects involvement is optional, so purely computational projects are fully within scope rather than being penalised for lacking a clinical arm. The trade-off is budget scale: 250,000 dollars per year in direct costs over at most 4 years is modest for an R01 and rules out large data-generation components.
This is a fit for method development, tool building and secondary analysis, not for assembling new cohorts.
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Or search similar grants →According to the current listing, eligibility includes: Eligible applicants are broad: higher education institutions (public and private, including foreign institutions), nonprofit organizations, for-profit organizations including small businesses, state, local, federal and tribal governments, and other organizations. Cost sharing is not required. Budgets are limited to 250,000 US dollars per year in direct costs with a maximum project period of 4 years. The activity code is R01 and the NOFO is clinical-trial-optional; human subjects involvement is also optional, so purely computational projects are eligible. Scope covers bioinformatics, translational bioinformatics and computational biology, with the NOFO explicitly seeking work that leverages transformative technologies including artificial intelligence, machine learning and large-scale computational platforms to extract knowledge from large, diverse and complex biological datasets, and specifically naming studies that use AI and ML applications for predictive and analytical bioinformatics research. Application due dates run on multiple rolling deadlines from 5 June 2026 through 5 February 2029, each at 5:00 PM local time of the applicant organization; NIH standard R01 due dates for new applications are 5 February, 5 June and 5 October, so the next date following September 2026 is 5 October 2026. The NOFO expires 6 March 2029. Applications are submitted through Grants.gov. Verify the current due dates, budget cap, clinical trial designation and any updated NOFO number on the official announcement before preparing an application, since NIH has moved publication of Notices of Funding Opportunity to Grants.gov. Confirm the full requirements in the official notice before applying.
The current listing shows the NOFO caps budgets at 250,000 US dollars per year in direct costs, with a maximum project period of 4 years. amount_min is set to 250,000 (one year at the ceiling) and amount_max to 1,000,000 (four years at the ceiling), both in direct costs. No minimum award is published, so smaller and shorter budgets are permitted and are common for method-development R01s at NLM. These figures are direct costs only - facilities and administrative costs are additional and are not counted against the 250,000 dollar annual cap, so the total cost of a fully budgeted four-year award will be materially higher than 1,000,000 dollars depending on the applicant institution's negotiated rate. Cost sharing is not required. Verify award ceilings, matching requirements, and allowable costs in the official notice.
Applications for NIH PAR-26-040 Advancing Bioinformatics, Translational Bioinformatics and Computational Biology Research (R01) for AI and Machine Learning in Biomedical Data are due October 5, 2026. Build your timeline backwards from this date to cover registrations, approvals, and final submission checks.
NIH PAR-26-040 Advancing Bioinformatics, Translational Bioinformatics and Computational Biology Research (R01) for AI and Machine Learning in Biomedical Data is funded by National Institutes of Health (NIH), National Library of Medicine (NLM). 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.
NIH NLM Institutional Grants for Research Training in Biomedical Informatics, Data Science, and AI RFA-LM-26-004 is sponsored by National Institutes of Health (NIH), National Library of Medicine (NLM). This institutional training grant program aims to build the research workforce in biomedical informatics, data science, and artificial intelligence. NLM funds universities and research institutions to run predoctoral and postdoctoral training programs that prepare researchers to apply computational and AI/ML methods to health and biomedical problems.
RFA-LM-26-004 is the National Library of Medicine's institutional training grant competition for predoctoral and postdoctoral programs in biomedical informatics, data science, and artificial intelligence and machine learning. NLM plans roughly 25 awards from a USD 12,000,000 pool, with awards between USD 500,000 and USD 775,000 and applications due 25 September 2026. The RFA covers both brand-new training programs and renewals of existing NLM-funded programs, which materially changes the competitive picture: incumbents with track records of trainee placement are competing in the same pool as new entrants, and new programs need to show institutional depth that renewals can simply document. NLM asks for cutting-edge, forward-looking training experiences that prepare trainees to attack complex health problems with computational methods, and explicitly values interdisciplinary designs that pull together computer science, statistics, clinical and biological perspectives rather than housing training inside a single department. This is one of the largest sustained federal pipelines for AI-in-health workforce development, and because it is a T-series institutional mechanism it is administered by the institution rather than an individual investigator. Estimated award date is 30 January 2027 with projects starting 1 July 2027.
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.
PAR-26-042 funds NLM-priority clinical informatics R01 grants up to $250,000 in direct costs per year through March 6, 2029, with standard NIH cycles on October 5, February 5, and June 5. The notice explicitly defines non-responsive applications: incremental tool improvements, projects primarily focused on social determinants of health, and projects primarily focused on ethical/legal/social issues. With NIH SBIR/STTR just reopened and the OMB Uniform Grants Regulation rewrite reshaping discretionary awards, the NLM clinical informatics line is one of the few stable, well-defined biomedical funding streams left at the agency. Here is how to read it.
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