NLM Institutional Grants for Research Training in Biomedical Informatics, Data Science, and AI

Q: When is the deadline for NLM Institutional Grants for Research Training in Biomedical Informatics, Data Science, and AI?

This is a forecast opportunity; the agency has not posted dates yet.

Q: Who is eligible for NLM Institutional Grants for Research Training in Biomedical Informatics, Data Science, and AI?

Eligible applicants: Private colleges & universities; Nonprofits (501(c)(3)); Tribal organizations; Public colleges & universities; Nonprofits without 501(c)(3) status; Tribal governments.

National Institutes of Health

Federal Grants for Science Research Grants for Education Capacity Building Grants

Funding Amount

$500,000 - $775,000

Deadline

Forecast — dates not yet posted

Number of Awards

Grant Type

Federal

Can we apply?

Check your organization against each line. Taken from the listing; confirm with the funder's guidelines.

Eligible organizations

Private colleges & universities
Nonprofits (501(c)(3))
Tribal organizations
Public colleges & universities
Nonprofits without 501(c)(3) status
Tribal governments

Overview

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.