Submission Deadline 10/02/2026
Fiscal Capacity $50,135,013
HHS-NIH11 Grant — Key Facts
Opportunity Number RFA-HD-27-006
Agency HHS-NIH11
Application Deadline 10/02/2026
Award Amount $50,135,013
Status Posted
Sector Health
Cost Sharing Not Required

Fiscal Parameters & Taxonomy

Authority HHS-NIH11
Status Posted

Who Can Apply

Nonprofits having a 501(c)(3) status with the IRS, other than institutions of higher education Native American tribal governments (Federally recognized) Small businesses Independent school districts County governments Others (see text field entitled "Additional Information on Eligibility" for clarification) Nonprofits that do not have a 501(c)(3) status with the IRS, other than institutions of higher education Native American tribal organizations (other than Federally recognized tribal governments) Special district governments Public and State controlled institutions of higher education State governments Private institutions of higher education For profit organizations other than small businesses City or township governments Public housing authorities/Indian housing authorities

Eligibility Intelligence

Refer to Section III. Eligibility Information in the NOFO for additional information on eligibility.Foreign Organizations/International Collaborations:Non-domestic (non-U.S.) Entities (Foreign Organization) are not eligible to apply.Non-domestic (non-U.S.) components of U.S. Organizations are not eligible to apply.Foreign components, as defined in the NIH Grants Policy Statement, are not allowed.

Program Description

This Notice of Funding Opportunity (NOFO) invites exploratory grant applications, hereafter referred to as the Novel Experiential Technologies Assisting Individual learning Hubs or NExT AI Hubs (formerly Learning Disabilities Innovation Hubs), to address the impact of Artificial Intelligence (AI) technologies on developmental outcomes in children diagnosed with or at risk for developing a specific learning disability (SLD) impacting reading, writing, and mathematics. NExT AI Hubs include a single Research Project and a Leadership Core that support the goals and aims of the Hub. This NOFO seeks to serve as a catalyst to 1) speed the maturation of nascent/novel, high-impact, high-risk research that advances understanding of the role AI technology plays in supporting, improving, or limiting the learning, cognitive, and socio-emotional needs of children at risk for or diagnosed with SLDs, 2) build an evidence base for the SLD community to inform policy or practice, and 3) provide project-embedded, career-enhancing research and professional development opportunities to support the next generation of transdisciplinary SLD scientists. This initiative provides opportunities to support planning and building a body of research and corresponding intellectual infrastructure to enable NExT AI investigators to compete for large research and program project opportunities in the future.This NOFO aims to integrate research topics that are of relevance to various research programs at the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) and align with the NICHD Strategic Plan. The NOFO intends to build cross-programmatic, transdisciplinary and cross-cutting scientific research, and critically nurture the development of early career investigators capable of conducting this research.

CFDA Programs

93.865 Child Health and Human Development Extramural Research

Agency Contact

nichd_cdbb_nofos@mail.nih.gov nichdgrantsmanagement@mail.nih.gov

✉ nichdgrantsmanagement@mail.nih.gov

📞 301-402-2541

Related Intelligence Guides

In-depth editorial guides covering this agency's programs, eligibility requirements, and application strategies.

GrantMetric Intelligence Systems — Independent federal grant intelligence platform. Not affiliated with Grants.gov, the U.S. Department of Health & Human Services, or any government agency. Grant data is sourced from the Grants.gov API for informational purposes only; always verify opportunity details directly with the funding agency before applying. Some links on this site are affiliate links — we may earn a commission at no additional cost to you. Full Disclaimer  ·  Last Reviewed: May 2026  ·  Data Methodology