Smart Health and Biomedical Research in the Era of Artificial Intelligence and Advanced Data Science
Title:  

Smart Health and Biomedical Research in the Era of Artificial Intelligence and Advanced Data Science

Agency:  

U.S. National Science Foundation

State:  

United States of America

NAICS Code:  

541710

Industry:  

Information Technology and Software Development

Solicitation Type:  

Grants Notice

Solicitation ID:  

25-542

Open Date:  

7/24/2025

Close Date:  

11/1/2025

Last Updated:  

8/21/2025

Description:
The purpose of this interagency program solicitation is to support the development of transformative high-risk, high-reward advances in computer and information science, engineering, mathematics, statistics, behavioral and/or cognitive research to address pressing questions in the biomedical and public health communities. * The program aims to develop novel methods to intuitively and intelligently collect, sense, connect, analyze and interpret data from individuals, devices and systems to enable discovery and optimize health. * Solutions to these complex biomedical or public health problems demand the formation of interdisciplinary teams that are ready to address these issues, while advancing fundamental science and engineering. * The program will support proposals from non-profit, non-academic organizations, institutions of higher education, and other eligible entities. * The estimated funding for this program is $20,000,000, with an award ceiling of $1,200,000.
Attached Files:

Please visit the bid source via the “Link to Bid Source” button below for documentation.

Contact Information:

Goli Yamini

sch-correspondence@nsf.gov

(703) 292-5367

Budget Estimate (AI):

$200,000 – $1,200,000

Based on the estimated funding for this program, which is $20,000,000, and the award ceiling of $1,200,000, the budget for this opportunity is likely to be in the range of $200,000 to $1,200,000. The actual budget will depend on the number of awards made and the specific proposals submitted. Factors that may influence the likely payment range include the number of eligible proposals, the quality of the proposals, and the availability of funds.

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