Institutional Grants for Research Training in Biomedical Informatics, Data Science, and AI
🏛 National Institutes of Health (HHS-NIH11)
✓ Free, no account · Source: Grants.gov · Last verified Jul 16, 2026
Can you apply?
This grant is for institutions offering research training in biomedical informatics, data science, and AI. Eligible applicants include academic medical centers, research universities, and medical schools. The grant supports institutional capacity to train the next generation of researchers in computational health and data-driven medicine. Geographic scope is nationwide. Funds may support fellowships, courses, mentorship, and infrastructure to develop workforce talent in these fields.
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Key dates
- Feb 18, 2026 Applications open
- Sep 25, 2026 Application deadline in 70 days
- Jan 30, 2027 Award announced
- Jul 1, 2027 Project start
Program description
The National Library of Medicine (NLM) 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 (AI/ML). NLM emphasizes cutting-edge, forward-looking training experiences that equip trainees to address complex health and biomedical challenges through advanced computational approaches. Applications may propose the creation of new training programs or the renewal of existing NLM-supported programs. These programs are designed to meet the growing demand for researchers with deep expertise in biomedical computing, data science, and AI/ML, with clear relevance to health and biomedical research. Recognizing the inherently interdisciplinary nature of these fields, NLM seeks programs that integrate methods and perspectives across disciplines to advance biomedical informatics, data science, and AI/ML.
Who can apply
Eligible applicants
How to apply
Application links
Key dates & requirements
Required documents
- SF-424 (Application for Federal Assistance)
- Project Narrative/Research Training Plan
- Institutional commitment letter
- Budget and budget narrative
- Curriculum vitae for key faculty
- Letters of support from mentors
- Trainee recruitment and selection plan
- Diversity and inclusion plan
Program contact
- 👤 NLM Extramural Programs
- 📧 NLMProgram@nih.gov
- 📞 Please contact via e-mail.
Funding track record
Recent awards under CFDA 93.879 from the last 3 years — real organizations that won funding through this same program.
Top 10 Largest Recent Awards
-
$31,424,450
-
$21,310,613
-
$18,962,515
-
$18,266,443
-
$14,828,350
-
$14,642,836
-
$13,681,359
-
$13,351,995
-
$12,454,032
-
$11,107,283
Top States by Funding
- MA 9 awards $61.2M
- NY 12 awards $58.1M
- TN 3 awards $50.1M
- TX 4 awards $36.4M
- CA 9 awards $25.5M
Source: USAspending.gov — federal spending transparency. Data covers last 3 years.
Funding history
Annual funding for this program — Federal obligations (CFDA 93.879). How funding has trended year over year.
| 2024 | $78,196,782 | |
| 2025 | $79,391,024 | |
| 2026 est. | $70,230,119 |
FAQ
Who is eligible to apply for this grant?
Academic institutions with research training programs in biomedical informatics, data science, or AI. Typically universities, medical schools, and research centers qualify.
What activities does this grant support?
Training programs for graduate students and postdocs. Includes fellowships, curriculum development, and mentorship infrastructure.
Is there a funding cap or typical award amount?
Federal training grants typically range from $100K-$500K annually. Check the detailed RFP for exact parameters.
How competitive is this grant?
Training grants are competitive. Strong institutional commitment and proven faculty expertise increase success chances significantly.
What is the application deadline?
Application opens February 18, 2026. Check NIH's Grants.gov page for specific submission deadlines and any rolling review dates.
💡 Tips for applicants
- Emphasize your institution's existing strength in biomedical informatics, data science, or AI research to demonstrate infrastructure readiness.
- Show clear career pathways for trainees post-graduation. Include employment data for previous program graduates.
- Develop a diverse trainee recruitment strategy. Address how your program will attract underrepresented groups in tech and biomedical research.
- Budget strategically for both trainee support (stipends/tuition) and faculty development to strengthen the training environment.
- Build strong letters of commitment from department leadership and key faculty mentors. Show institutional investment beyond grant funds.
⚠️ Common mistakes
Weak institutional commitment letters. Proposals lacking evidence of existing research strength in target fields. Unclear trainee selection criteria or insufficient diversity recruitment plans.
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