Statistics | PD 18 1269

Opportunity Information: Apply for PD 18 1269

The National Science Foundation (NSF) is offering a discretionary grant opportunity titled "Statistics" (Funding Opportunity Number: PD 18-1269) under its Science and Technology and other Research and Development activity category (CFDA: 47.049). This program is aimed at supporting research that advances the foundations and practice of statistical science, with an emphasis on both core statistical theory and the development of statistical methods that can be applied across essentially any area of science or engineering. The opportunity is designed to fund work that strengthens how researchers model randomness, learn from data, and quantify uncertainty, all of which are central to making reliable scientific and engineering advances.

The focus of the program spans two tightly connected areas: statistical theory and statistical methods. On the theory side, the program supports work that builds the mathematical and conceptual foundations of statistics, such as understanding the properties of estimators, inference procedures, and learning algorithms, and clarifying when and why particular approaches succeed or fail. This theoretical base is presented as essential to the broader field because it underpins the credibility and generalizability of statistical conclusions. On the methods side, the program supports research that creates or improves practical techniques for stochastic modeling and for the collection, analysis, and interpretation of data. In plain terms, this includes developing new tools for designing studies and experiments, extracting signal from noisy measurements, and translating data into defensible conclusions.

A central theme throughout the opportunity is uncertainty quantification. The NSF description highlights that statistical methods should not just produce answers, but should also characterize the uncertainty inherent in the data and the modeling assumptions. This can include, for example, improved methods for confidence intervals, hypothesis testing, Bayesian posterior summaries, prediction intervals, model checking, and robustness to misspecification. By treating uncertainty as a first-class output, the program aims to support research that makes downstream scientific and engineering decisions more trustworthy and better calibrated to the limits of what the data can support.

The program explicitly welcomes a wide range of project structures, from single-investigator proposals to interdisciplinary team projects. This signals that NSF is open to both focused foundational contributions and larger collaborative efforts that bring statisticians together with domain scientists or engineers. Because the solicitation emphasizes applicability to any domain of science and engineering, strong proposals could involve methodological advances motivated by real data challenges in fields such as biology, medicine, environmental science, materials, social science, cybersecurity, manufacturing, or artificial intelligence, as long as the statistical contribution is substantive and generalizable beyond one narrow case.

Eligibility is listed as unrestricted, indicating that the applicant pool is broad and not limited to a particular institution type in the provided summary fields. The original closing date shown is December 16, 2024. The listing does not provide an award ceiling or an expected number of awards in the supplied source data, so prospective applicants would need to consult the full NSF program page or the current solicitation details for up-to-date information on typical award sizes, durations, and portfolio priorities. Overall, the opportunity is best understood as support for research that advances statistical thinking and tool-building, with the long-term goal of improving how science and engineering use data to learn, predict, and make decisions under uncertainty.

• The National Science Foundation in the science and technology and other research and development sector is offering a public funding opportunity titled "Statistics" and is now available to receive applicants.
• Interested and eligible applicants and submit their applications by referencing the CFDA number(s): 47.049.
• This funding opportunity was created on 2018-03-29.
• Applicants must submit their applications by 2024-12-16. (Agency may still review applications by suitable applicants for the remaining/unused allocated funding in 2026.)
• Eligible applicants include: Unrestricted.

Apply for PD 18 1269

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