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Find similar grantsGrant for Mathematical Foundations of Artificial Intelligence Research is sponsored by See official notice (listed on The Grant Portal). This funding opportunity supports research in the mathematical foundations of artificial intelligence. While not explicitly tied to astronomy, fundamental AI research could have applications in the field.
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gov Maintenance Calendar View similar opportunities Mathematical Foundations of Artificial Intelligence U.S. National Science Foundation U.S. National Science Foundation Document Type:Grants Notice Funding Opportunity Number:24-569 Funding Opportunity Title:Mathematical Foundations of Artificial Intelligence Opportunity Category:Discretionary Opportunity Category Explanation: Funding Instrument Type:Grant Category of Funding Activity:Science and Technology and other Research and Development Expected Number of Awards: Assistance Listings:47.
041 -- Engineering 47. 049 -- Mathematical and Physical Sciences 47. 070 -- Computer and Information Science and Engineering 47.
075 -- Social, Behavioral, and Economic Sciences Cost Sharing or Matching Requirement:No Last Updated Date:Oct 18, 2025 Original Closing Date for Applications:Oct 10, 2024 Current Closing Date for Applications:Oct 09, 2026 Archive Date:Nov 08, 2026 Estimated Total Program Funding:$ 8,500,000 Eligible Applicants:Others (see text field entitled "Additional Information on Eligibility" for clarification) Additional Information on Eligibility:*Who May Submit Proposals: Proposals may only be submitted by the following: -Non-profit, non-academic organizations: Independent museums, observatories, research laboratories, professional societies and similar organizations located in the U.S. that are directly associated with educational or research activities.
- <span>Institutions of Higher Education (IHEs) - Two- and four-year IHEs (including community colleges) accredited in, and having a campus located in the US, acting on behalf of their faculty members.
</span> *Who May Serve as PI: <div class="OutlineElement Ltr SCXW177155816 BCX0"><p class="Paragraph SCXW177155816 BCX0"><span class="TrackChangeTextInsertion TrackedChange SCXW177155816 BCX0"><span class="TextRun SCXW177155816 BCX0" lang="EN-US" xml:lang="EN-US" data-contrast="none"><span class="NormalTextRun SCXW177155816 BCX0">As of the date the proposal is </span><span class="NormalTextRun SCXW177155816 BCX0">submitted</span><span class="NormalTextRun SCXW177155816 BCX0">, any PI, co-PI, or senior/key personnel must hold either:</span></span></span><span class="EOP TrackedChange SCXW177155816 BCX0" data-ccp-props="{"></span><ul><li><span class="TrackChangeTextInsertion TrackedChange SCXW177155816 BCX0"><span class="TextRun SCXW177155816 BCX0" lang="EN-US" xml:lang="EN-US" data-contrast="none">a tenured or tenure-track position, </span></span><span class="TrackChangeTextInsertion TrackedChange SCXW177155816 BCX0"><span class="TextRun SCXW177155816 BCX0" lang="EN-US" xml:lang="EN-US" data-contrast="none">or</span></span><span class="EOP TrackedChange SCXW177155816 BCX0" data-ccp-props="{"></span></li><li><span class="TrackChangeTextInsertion TrackedChange SCXW177155816 BCX0"><span class="TextRun SCXW177155816 BCX0" lang="EN-US" xml:lang="EN-US" data-contrast="none">a primary, full-time, paid appointment in a research or teaching position</span></span></li></ul><span class="TrackChangeTextInsertion TrackedChange SCXW177155816 BCX0"><span class="TextRun SCXW177155816 BCX0" lang="EN-US" xml:lang="EN-US" data-contrast="none"><span class="NormalTextRun SCXW177155816 BCX0">at a US-based campus of an organization eligible to </span><span class="NormalTextRun SCXW177155816 BCX0">submit</span><span class="NormalTextRun SCXW177155816 BCX0"> to this solicitation (see above), with exceptions granted for family or medical leave, as </span><span class="NormalTextRun SCXW177155816 BCX0">determined</span><span class="NormalTextRun SCXW177155816 BCX0"> by the </span><span class="NormalTextRun SCXW177155816 BCX0">submitting</span><span class="NormalTextRun SCXW177155816 BCX0"> organization.
Individuals with </span></span></span><span class="TrackChangeTextInsertion TrackedChange SCXW177155816 BCX0"><span class="TextRun SCXW177155816 BCX0" lang="EN-US" xml:lang="EN-US" data-contrast="none">primary</span></span><span class="TrackChangeTextInsertion TrackedChange SCXW177155816 BCX0"><span class="TextRun SCXW177155816 BCX0" lang="EN-US" xml:lang="EN-US" data-contrast="none"> appointments at for-profit non-academic organizations or at overseas branch campuses of U.S. institutions of higher education are not eligible.
</span></span><span class="EOP TrackedChange SCXW177155816 BCX0" data-ccp-props="{"></span></div> ## Additional Information Agency Name:U.S. National Science Foundation Description:Machine Learning and Artificial Intelligence (AI) are enabling extraordinary scientific breakthroughs in fields ranging from protein folding, natural language processing, drug synthesis, and recommender systems to the discovery of novel engineering materials and products.
These achievements lie at the confluence of mathematics, statistics, engineering and computer science, yet a clear explanation of the remarkable power and also the limitations of such AI systems has eluded scientists from all disciplines. Critical foundational gaps remain that, if not properly addressed, will soon limit advances in machine learning, curbing progress in artificial intelligence.
It appears increasingly unlikely that these critical gaps can be surmounted with increased computational power and experimentation alone. Deeper mathematical understanding is essential to ensuring that AI can be harnessed to meet the future needs of society and enable broad scientific discovery, while forestalling the unintended consequences of a disruptive technology.
The National Science Foundation Directorates for Mathematical and Physical Sciences (MPS), Computer and Information Science and Engineering (CISE), Engineering (ENG), and Social, Behavioral and Economic Sciences (SBE) will jointly sponsor research collaborations consisting of mathematicians, statisticians, computer scientists, engineers, and social and behavioral scientists focused on the mathematical and theoretical foundations of AI.
Research activities should focus on the most challenging mathematical and theoretical questions aimed at understanding the capabilities, limitations, and emerging properties of AI methods as well as the development of novel, and mathematically grounded, design and analysis principles for the current and next generation of AI approaches.
Specific research goals include: establishing a fundamental mathematical understanding of the factors determining the capabilities and limitations of current and emerging generation s of AI systems, including, but not limited to, foundation models, generative models, deep learning, statistical learning, federated learning, and other evolving paradigms; the development of mathematically grounded design and analysis principles for the current and next generations of AI systems; rigorous approaches for characterizing and validating machine learning algorithms and their predictions; research enabling provably reliable, translational, general-purpose AI systems and algorithms; e ncouragement of new collaborations in this interdisciplinary research community and between institution s.
The overall goal is to establish innovative and principled design and analysis approaches for AI technology using creative yet theoretically grounded mathematical and statistical frameworks, yielding explainable and interpretable models that can enable sustainable, socially responsible, and trustworthy AI.
Link to Additional Information:NSF Publication 24-569 Grantor Contact Information:If you have difficulty accessing the full announcement electronically, please contact: If you have any problems linking to this funding announcement, please contact the email address above. ## Similar Opportunities (identified by AI) #### Health & Human Services * Frequently Asked Questions ## Your session will expire in 3 minutes.
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Applications for Grant for Mathematical Foundations of Artificial Intelligence Research are due October 9, 2026. Build your timeline backwards from this date to cover registrations, approvals, and final submission checks.
Grant for Mathematical Foundations of Artificial Intelligence Research is funded by See official notice (listed on The Grant Portal). Verify program details on the funder's official page before applying.
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