Skip to content
Open·Synced from source July 16, 2026

Mathematical Foundations of Artificial Intelligence

U.S. National Science Foundation

Apply at U.S. National Science Foundation

Free. Verify your email, then we send one reminder only.

Posted
Dec 17, 2025
Amount
$500,000 - $1,500,000
Closes
Oct 9, 2026 (in 85 days)
Last verified
Jul 16, 2026

Classification and identifiers

Solicitation number
24-569
Assistance listing (CFDA)
47.070

Amount

$500,000 - $1,500,000

Who can apply

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. 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. *Who May Serve as PI: As of the date the proposal is submitted, any PI, co-PI, or senior/key personnel must hold either: a tenured or tenure-track position, or a primary, full-time, paid appointment in a research or teaching position at a US-based campus of an organization eligible to submi...

About this opportunity

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...

Refine this search