Explore Ai Data Science Grants Nationwide

The grant aims to establish a pilot funding program that leverages advancements in data science and AI to address the challenges of diabetes research by integrating complex data and developing AI models for personalized approaches to the disease. Eligible applicants include multidisciplinary teams with expertise in both diabetes and data science, specifically targeting the University of California, San Diego. Application details are not explicitly provided, but all submissions will undergo peer review, and only meritorious applications will be considered for funding.

The purpose of this grant is to develop and test an AI- or ML-based algorithmic real-world data model for post-market surveillance of complex generic drug products to ensure therapeutic equivalence and inform regulatory decisions. Eligible applicants include various nonprofit organizations, government entities, for-profit organizations, and educational institutions. Applicants may submit multiple distinct applications, but the FDA will not accept overlapping submissions; for more information, contact terrin.brown@fda.hhs.gov.

The NIH Common Fund is preparing to publish a Notice of Funding Opportunity (NOFO) for the PRIMED-AI program, aimed at developing AI-based tools that integrate clinical imaging with various health data to improve personalized medicine for patients with chronic conditions. Eligible applicants include government entities, educational institutions, nonprofits, and for-profit organizations. While applications are not currently being accepted, interested parties are encouraged to start forming collaborations and developing projects in anticipation of the upcoming NOFO.

The NIH Common Fund is launching the PRIMED-AI program to develop AI-based tools that integrate clinical imaging with various health data types to improve personalized medicine for patients with chronic conditions. Eligible applicants include public and private higher education institutions, nonprofits, government entities, and businesses. Although applications are not currently being accepted, interested parties are encouraged to prepare for future submissions and can contact the program via email for more information.

The grant aims to solicit research proposals for artificial intelligence development to support the U.S. Army Artificial Intelligence Integration Center (AI2C), focusing on basic, applied, and advanced research. Eligible applicants include institutions of higher education, nonprofit organizations, state and local governments, foreign entities, and for-profit organizations. To apply, interested parties must submit proposals in response to the Broad Agency Announcement (BAA) for competitive selection.

The NIH Common Fund is preparing to release a Notice of Funding Opportunity (NOFO) for the PRIMED-AI program, aimed at developing AI-based tools that integrate clinical imaging with various health data to improve personalized medicine for patients with chronic conditions. Eligible applicants include public and private higher education institutions, nonprofits, government entities, and businesses. Although applications are not currently being accepted, interested parties are encouraged to start forming collaborations and project ideas in anticipation of the NOFO's release.

The Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) aims to advance research on the effects of Artificial Intelligence (AI) technologies on developmental outcomes in children at risk for specific learning disabilities through the NExT AI Hubs initiative. Eligible applicants include state and county governments, federally recognized Native American tribal governments, public and private higher education institutions, independent school districts, nonprofits with 501(c)(3) status, and for-profit organizations. For application details, interested parties can contact the grantor via email at virginia.salo@nih.gov.

The NIH Common Fund is launching the PRIMED-AI program to develop AI-based tools that integrate clinical imaging with other health data to improve personalized medicine for patients with chronic conditions. Eligible applicants include government entities, educational institutions, nonprofits, and for-profit organizations. While applications are not currently being accepted, interested parties are encouraged to prepare collaborative projects and consider applying once the Notice of Funding Opportunity is published.

The NIH Common Fund is preparing to publish a Notice of Funding Opportunity (NOFO) for the PRIMED-AI program, aimed at developing AI-based tools that integrate clinical imaging with various health data to improve personalized medicine for patients with chronic conditions. Eligible applicants include government entities, educational institutions, nonprofits, and for-profit organizations, with a focus on those experienced in analyzing large multimodal datasets. While applications are not currently being solicited, interested parties are encouraged to prepare collaborations and projects in anticipation of the NOFO release.

The grant aims to enhance the capacity of researchers in addiction-related data science by supporting small-scale projects that apply innovative data science methods to address specific research questions. Eligible applicants include various nonprofit organizations, government entities, educational institutions, and for-profit organizations, with a focus on those serving diverse communities. To apply, interested investigators should propose projects that utilize existing datasets and adhere to ethical research practices, although specific application instructions are not provided in the summary.

The grant aims to support research collaborations that address the mathematical and theoretical foundations of artificial intelligence (AI), focusing on understanding its capabilities, limitations, and developing principled design and analysis approaches. Eligible applicants include non-profit organizations and institutions of higher education in the U.S., with specific requirements for principal investigators. Application details are not provided in the description.

The Human Networks and Data Science program (HNDS) aims to enhance the understanding of human behavior through data and network science research, focusing on dynamic data to address fundamental questions about individual and group behavior, with an emphasis on health, prosperity, and security. Eligibility is unrestricted, allowing a wide range of applicants to participate. Specific application procedures are not detailed in the description, but interested parties may contact NSF grants.gov support for assistance.