NLM Institutional Grants for Research Training in Biomedical Informatics, Data Science, and AI (T15 Independent Clinical Trial Not Allowed)
National Institutes of Health
Award ceiling
—Award floor
—Posted
Oct 16, 2026Closes
Feb 11, 2027Location eligibility
No specific state restriction found in this listing — check the full opportunity for details.Categories: Health
Eligible applicants: Nonprofits that do not have a 501(c)(3) status with the IRS, other than institutions of higher education, Private institutions of higher education, Nonprofits having a 501(c)(3) status with the IRS, other than institutions of higher education, Public and State controlled institutions of higher education, Public housing authorities/Indian housing authorities, County governments, Small businesses, City or township governments, Special district governments, Native American tribal organizations (other than Federally recognized tribal governments), For profit organizations other than small businesses, State governments, Native American tribal governments (Federally recognized), Independent school districts, Others (see text field entitled "Additional Information on Eligibility" for clarification)
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.