[U.S. National Science Foundation](https://www.nsf.gov)

December 15, 2026

No specified ceiling or floor; award size and duration vary by project.

Supports research in statistical theory, methods, and applications across all domains of science and engineering.

--- ## Description This program supports research in statistical theory and methods, including the development and application of statistical methods to any domain of science and engineering. The program welcomes a wide range of proposals, from single-investigator projects to interdisciplinary team efforts, aimed at advancing stochastic modeling, data collection, analysis, interpretation, and the characterization of uncertainty. The overarching goal is to facilitate scientific and engineering advancement through innovative statistical research. --- ## Due Dates - December 15, 2026 --- ## Funding Amount - No specific minimum or maximum award amount is stated. - Typical award size and duration depend on the scope and scale of the proposed research. - No cost sharing or matching is required. --- ## Eligibility - Open to all applicant types ("Unrestricted"), including: - Academic institutions - Nonprofit organizations - For-profit organizations - Government agencies - Individuals, subject to NSF policies - Proposals must comply with the [NSF Proposal & Award Policies & Procedures Guide (PAPPG)](https://www.nsf.gov/policies/pappg). --- ## Application Process - Proposals must be submitted through [Grants.gov](https://www.grants.gov/search-results-detail/302271) or via the NSF FastLane or Research.gov systems. - All applications must adhere to the requirements in the current [NSF PAPPG](https://www.nsf.gov/policies/pappg). - Review the [program page](http://www.nsf.gov/funding/pgm_summ.jsp?pims_id=5556) for detailed instructions and updates. - Contact program officers for guidance as needed. --- ## Additional Information - Awards are subject to NSF’s financial assistance award conditions effective October 1, 2024. - Proposers must comply with updated NSF research security policies, including new training and certification requirements. - The program encourages interdisciplinary collaborations and projects that advance the foundations and applications of statistics. --- ## External Links - [NSF Program Page: Statistics](http://www.nsf.gov/funding/pgm_summ.jsp?pims_id=5556) - [NSF Funding Opportunity on Grants.gov](https://www.grants.gov/search-results-detail/302271) - [NSF Proposal & Award Policies & Procedures Guide (PAPPG)](https://www.nsf.gov/policies/pappg) - [Browse funded projects](https://www.nsf.gov/awardsearch/search-results?ProgEleCode=126900&BooleanElement=Any&BooleanRef=Any&ActiveAwards=true#results) --- ## Contact Information | Name | Email | Phone | Organization | |---------------------|-----------------------------|-----------------|--------------| | Yong Zeng | [yzeng@nsf.gov](mailto:yzeng@nsf.gov) | (703) 292-7299 | MPS/DMS | | John E. Kolassa | [jkolassa@nsf.gov](mailto:jkolassa@nsf.gov) | (703) 292-4733 | MPS/DMS | | Tapabrata Maiti | [tmaiti@nsf.gov](mailto:tmaiti@nsf.gov) | (703) 292-5307 | MPS/DMS | | Jun Zhu | [jzhu@nsf.gov](mailto:jzhu@nsf.gov) | (703) 292-4551 | MPS/DMS | | NSF Grants.gov Support | [grantsgovsupport@nsf.gov](mailto:grantsgovsupport@nsf.gov) | | | | NSF General Info | [info@nsf.gov](mailto:info@nsf.gov) | 1-703-292-5111 | NSF |

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