Funding Opportunities

Early Career Faculty (ECF) is an appendix to the Space Technology Mission Directorate (STMD) NASA Research Announcement (NRA), titled “Space Technology Research, Development, Demonstration, and Infusion 2025 (SpaceTech REDDI 2025).” 

The Appendix seeks proposals from accredited U.S. universities on behalf of outstanding early-career faculty members who are beginning independent research careers. ECF is intended to accelerate the development of groundbreaking, high-risk/high-payoff space technologies to support future civil space applications, including space exploration, science, and commercial applications. Grants will be funded up to $250,000 each per year, with a maximum duration of three years. 

Due: July 10, 2025 

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.  

Due: October 10, 2025

A key focus of the design of modern computing systems is performance and scalability, particularly in light of the limits of Moore’s Law and Dennard scaling. To this end, systems are increasingly being implemented by composing heterogeneous computing components and continually changing memory systems as novel, performant hardware surfaces. Applications fueled by rapid strides in machine learning, data analysis, and extreme-scale simulation are becoming more domain-specific and highly distributed. In this scenario, traditional boundaries between hardware-oriented and software-oriented disciplines are increasingly blurred.

Due: Fourth Monday in January annually.

The Division of Mathematical Sciences (DMS) in the Directorate for Mathematical and Physical Sciences (MPS) at the National Science Foundation (NSF) and the Air Force Office of Scientific Research (AFOSR) plan to jointly support foundational mathematical and statistical research on Digital Twins in applied sciences. Recent years have witnessed a significant increase in the demand and interest in applications that involve collaborative teams developing and analyzing Digital Twins to support decision making in various fields, including science, engineering, medicine, urban planning, and more. Both agencies recognize the need to promote research aiming to stimulate an interplay between mathematics/statistics/computation and practical applications in the realm of Digital Twins.  This program encourages new collaborative efforts within the realm of Digital Twins, aiming at stimulating fundamental research innovation, pushing, and expanding the boundaries of knowledge, and exploring new frontiers in mathematics and computation for Digital Twin development, and its applications.  By leveraging this synergy, the program aims to harness science, technology, and innovation to address some of our Society’s most pressing challenges.

Due: March 15th annually