OpportunityTitle: Advanced Training in Artificial Intelligence for Precision Nutrition Science Research (AIPrN)  Institutional Research Training Programs (T32)
AdditionalInformationOnEligibility: Other Eligible Applicants include the following:  Alaska Native and Native Hawaiian Serving Institutions; Asian American Native American Pacific Islander Serving Institutions (AANAPISISs); Eligible Agencies of the Federal Government; Faith-based or Community-based Organizations; Hispanic-serving Institutions; Historically Black Colleges and Universities (HBCUs); Indian/Native American Tribal Governments (Other than Federally Recognized); Non-domestic (non-U.S.) Entities (Foreign Organizations); Regional Organizations; Tribally Controlled Colleges and Universities (TCCUs) ; U.S. Territory or Possession; Non-domestic (non-U.S.) Entities (Foreign Institutions) are not eligible to apply.     Non-domestic (non-U.S.) components of U.S. Organizations are not eligible to apply.
Description: The National Institutes of Health (NIH) Office of Nutrition Research (ONR) and participating NIH Institutes and Centers (ICs) intend to publish a Funding Opportunity Announcement (FOA) for new applications that will support new institutional research training programs (predoctoral, postdoctoral or both) in artificial intelligence (AI) for precision nutrition (AIPrN) that will focus on integration of the domains of precision nutrition, AI including machine learning (ML), systems biology, systems science, Big Data, and computational analytics. The goal is to build a future workforce that will be able to use growing data resources to tackle complex biomedical challenges in nutrition science that are beyond human intuition. It is hoped such research will lead to the development of innovative solutions to combat diet-related chronic diseases within the mission areas of the participating ICs. The vision of the AIPrN training program is to support the development of a diverse research workforce capable who will possess advanced competencies in AI including machine learning and data science analytics to apply to an increasingly complex landscape of Big Data from the molecular, to organismal, to community and societal scales related to nutrition and diet related conditions.
GrantorContactEmailDescription: See Section VII. Agency Contacts within the full opportunity announcement for all other inquires.
GrantorContactText: NIH Grants Information&lt;br/&gt;grantsinfo@nih.gov