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The National Library of Medicine invites applications for innovative predoctoral and postdoctoral training programs that prepare the next generation of researchers in biomedical informatics, data science, and artificial intelligence/machine learning.
This funding opportunity (RFA-LM-26-004) supports institutions in developing cutting-edge training curricula that equip trainees to address complex health and biomedical challenges through advanced computational approaches including AI/ML. Applicants may propose new training programs or seek renewal of existing NLM-supported initiatives. Awards are expected to begin January 30, 2027, with project start dates of July 1, 2027.
The program is part of NIH Assistance Listing 93. 879 (Medical Library Assistance). Cost sharing is not required.
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Or search similar grants →According to the current listing, eligibility includes: Private and public institutions of higher education, nonprofits (both 501(c)(3) and non-501(c)(3)), and federally recognized Native American tribal governments. Foreign institutions are not eligible. Confirm the full requirements in the official notice before applying.
The current listing shows $12 million total estimated program funding for 25 awards. Individual awards range from $500,000 to $775,000. Verify award ceilings, matching requirements, and allowable costs in the official notice.
Applications for NLM Institutional Grants for Research Training in Biomedical Informatics Data Science and Artificial Intelligence are due September 25, 2026. Build your timeline backwards from this date to cover registrations, approvals, and final submission checks.
NLM Institutional Grants for Research Training in Biomedical Informatics Data Science and Artificial Intelligence is funded by National Library of Medicine (NLM), National Institutes of Health. 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.
PHS 2023-2 Omnibus Solicitation of the NIH, CDC and FDA for Small Business Innovation Research Grant Applications (Parent SBIR [R43/R44] Clinical Trial Not Allowed) is sponsored by National Library of Medicine (NLM), National Institutes of Health (NIH). This omnibus solicitation supports small businesses engaging in research and development in biomedical informatics and data science, leading to commercialization.
PHS 2023-2 Omnibus Solicitation of the NIH for Small Business Technology Transfer Grant Applications (Parent STTR [R41/R42] Clinical Trial Not Allowed) is sponsored by National Library of Medicine (NLM), National Institutes of Health (NIH). This solicitation supports cooperative research and development projects between small business concerns and research institutions in biomedical informatics and data science.
The Department of Defense FY2026 Defense University Research Instrumentation Program (DURIP) provides funding for U.S. universities to acquire research equipment and instrumentation in areas important to national defense, including AI and machine learning hardware. The program is administered jointly by the Army Research Office (ARO), Office of Naval Research (ONR), and Air Force Office of Scientific Research (AFOSR), with approximately $34 million available and 95 awards anticipated. DURIP funds the acquisition of specialized computing hardware for AI/ML research (GPU clusters, TPUs, neuromorphic processors), robotics and autonomous systems testbeds, sensor arrays and data collection systems for machine learning training, high-performance computing infrastructure for defense-relevant AI research, and laboratory equipment for human-AI interaction studies. The program specifically supports equipment that enhances research-related education in DoD-priority disciplines. While general-purpose computing is not eligible, computing equipment directly supporting DoD-relevant AI research programs qualifies. No cost sharing is required.
Vinnova, Sweden's national innovation agency, funds projects developing applied AI solutions for Swedish industry through its Advanced Digitalization Programme. Each project can apply for between 2 and 10 million SEK (approximately $190,000 to $950,000 USD) covering up to 50% of eligible project costs. The total call budget is 60 million SEK. Projects run for 12-24 months and focus on two key areas: Intelligent Edge (AI for real-time application in the sensor chain) and AI-based decision support. All projects must address industrial needs and integrate gender equality and climate change perspectives. Scientific publications must be open access. A parallel call also funds AI and cybersecurity projects at 1-10 million SEK per project with a 50 million SEK total budget.
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.
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 articleARPA-H launched SPECTRA on September 17, 2026 under solicitation ARPA-H-SOL-26-163 — four technical areas with separate Solution Summary deadlines on October 18, December 2, and January 18. The enabling-technologies area closes first, five weeks after launch. Here is why the sequencing matters and how to read each TA.
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