2345874
Project Grant
Overview
Grant Description
NRT-AI: Enabling AI on the fly - Artificial intelligence (AI) is fundamentally reconfiguring the engines of scientific discovery, technological innovation, and industrial manufacturing that fuel modern economies.
Excitement for revolutionary advances in this domain is tempered, however, by unsettling changes to the nature of human work and fears of compounding social inequities.
Additionally, current AI is founded on ad hoc designs, sub-optimal links to foundational mathematics and computing theory, and poorly considered demands on energy sources.
This National Science Foundation Research Traineeship (NRT) award to Texas A&M University will address these shortcomings and demands by training graduate master’s and doctoral students in the interdisciplinary fields of the mathematical, molecular, and materials foundations of AI.
This effort anticipates training adaptive changemakers who will design AI to work with people and educate people to work with AI.
The project anticipates fostering a culture of team science and community engagement by training sixty-seven (67) MS and PhD students, including nineteen (19) funded trainees, from graduate programs in statistics and mathematics, electrical and computer engineering, computer science, chemistry, materials science and engineering, mechanical engineering, and interdisciplinary education.
Trainees will work at the intersection of foundational theory, AI algorithms, neuromorphic (human brain-inspired) materials discovery, and analog circuit design to close the AI for materials & circuits with the materials & circuits for AI loop.
The traineeship will exponentially amplify the impact of AI by designing and creating new materials and computing architectures.
Through close interactions within a rich ecosystem and communities, this project will help attain the full potential of AI to uplift communities, democratize scientific and technological discoveries, empower a more equitable information economy, and build societal trust by emphasizing the theme of “better together,” i.e., humans and AI working in concert to realize human potential.
Furthermore, the traineeship will serve as a test bed for a transformative doctoral education model with essential components for innovative graduate education that will be customized, iterated, refined, scaled, and sustained.
The project will develop a new graduate professional certificate and will further devise a skills and experiences pathway that will be expanded across graduate and professional programs.
Ultimately, this project will advance new M.S. and Ph.D. training models steeped in a rich and diverse regional innovation ecosystem related to AI and semiconductor manufacturing that will serve as a blueprint for other institutions.
The NSF Research Traineeship (NRT) program is designed to encourage the development and implementation of bold, new potentially transformative models for STEM graduate education training.
The program is dedicated to effective training of STEM graduate students in high priority interdisciplinary or convergent research areas through comprehensive traineeship models that are innovative, evidence-based, and aligned with changing workforce and research needs.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the foundation's intellectual merit and broader impacts review criteria.
Subawards are planned for this award.
Excitement for revolutionary advances in this domain is tempered, however, by unsettling changes to the nature of human work and fears of compounding social inequities.
Additionally, current AI is founded on ad hoc designs, sub-optimal links to foundational mathematics and computing theory, and poorly considered demands on energy sources.
This National Science Foundation Research Traineeship (NRT) award to Texas A&M University will address these shortcomings and demands by training graduate master’s and doctoral students in the interdisciplinary fields of the mathematical, molecular, and materials foundations of AI.
This effort anticipates training adaptive changemakers who will design AI to work with people and educate people to work with AI.
The project anticipates fostering a culture of team science and community engagement by training sixty-seven (67) MS and PhD students, including nineteen (19) funded trainees, from graduate programs in statistics and mathematics, electrical and computer engineering, computer science, chemistry, materials science and engineering, mechanical engineering, and interdisciplinary education.
Trainees will work at the intersection of foundational theory, AI algorithms, neuromorphic (human brain-inspired) materials discovery, and analog circuit design to close the AI for materials & circuits with the materials & circuits for AI loop.
The traineeship will exponentially amplify the impact of AI by designing and creating new materials and computing architectures.
Through close interactions within a rich ecosystem and communities, this project will help attain the full potential of AI to uplift communities, democratize scientific and technological discoveries, empower a more equitable information economy, and build societal trust by emphasizing the theme of “better together,” i.e., humans and AI working in concert to realize human potential.
Furthermore, the traineeship will serve as a test bed for a transformative doctoral education model with essential components for innovative graduate education that will be customized, iterated, refined, scaled, and sustained.
The project will develop a new graduate professional certificate and will further devise a skills and experiences pathway that will be expanded across graduate and professional programs.
Ultimately, this project will advance new M.S. and Ph.D. training models steeped in a rich and diverse regional innovation ecosystem related to AI and semiconductor manufacturing that will serve as a blueprint for other institutions.
The NSF Research Traineeship (NRT) program is designed to encourage the development and implementation of bold, new potentially transformative models for STEM graduate education training.
The program is dedicated to effective training of STEM graduate students in high priority interdisciplinary or convergent research areas through comprehensive traineeship models that are innovative, evidence-based, and aligned with changing workforce and research needs.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the foundation's intellectual merit and broader impacts review criteria.
Subawards are planned for this award.
Awardee
Funding Goals
THE GOAL OF THIS FUNDING OPPORTUNITY, "NATIONAL SCIENCE FOUNDATION RESEARCH TRAINEESHIP (NRT) PROGRAM", IS IDENTIFIED IN THE LINK: HTTPS://WWW.NSF.GOV/PUBLICATIONS/PUB_SUMM.JSP?ODS_KEY=NSF21536
Grant Program (CFDA)
Awarding Agency
Place of Performance
College Station,
Texas
77843-3255
United States
Geographic Scope
Single Zip Code
Related Opportunity
Analysis Notes
Amendment Since initial award the total obligations have increased from $3,000,000 to $3,025,000.
Texas A & M University was awarded
NRT-AI: Transforming STEM Graduate Education
Project Grant 2345874
worth $3,025,000
from the Division of Research on Learning in Formal and Informal Settings in September 2024 with work to be completed primarily in College Station Texas United States.
The grant
has a duration of 5 years and
was awarded through assistance program 47.076 Education and Human Resources.
The Project Grant was awarded through grant opportunity National Science Foundation Research Traineeship (NRT) Program.
Status
(Ongoing)
Last Modified 1/7/26
Period of Performance
9/1/24
Start Date
8/31/29
End Date
Funding Split
$3.0M
Federal Obligation
$0.0
Non-Federal Obligation
$3.0M
Total Obligated
Activity Timeline
Transaction History
Modifications to 2345874
Additional Detail
Award ID FAIN
2345874
SAI Number
None
Award ID URI
SAI EXEMPT
Awardee Classifications
Public/State Controlled Institution Of Higher Education
Awarding Office
491101 DIVISION OF GRADUATE EDUCATION
Funding Office
491109 DIV OF RESEARCH ON LEARNING IN
Awardee UEI
JF6XLNB4CDJ5
Awardee CAGE
1T3H7
Performance District
TX-10
Senators
John Cornyn
Ted Cruz
Ted Cruz
Modified: 1/7/26