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Why did the Division of Earth Sciences (EAR) realign its science funding programs?

EAR realigned its science funding programs to better serve the research community. The nature of EAR-supported science is changing, with more projects that span multiple domains of Earth Science research. By having programs with broader scopes, EAR is making it simpler to find a home for a given research project. The realignment of programs is designed to more readily support disciplinary, multidisciplinary, and interdisciplinary science. The new programmatic structure also will provide greater flexibility for EAR to support projects encompassing a wider range of award sizes and scopes.

What happened to my program?

While the EAR programs have changed names and structure, the disciplines that the division supports have not changed.

I currently have a proposal under review in an EAR program, but now that program has been archived. What happens

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U.S. National Science Foundation

Directorate for Geosciences
     Division of Earth Sciences

Full Proposal Deadline(s) (due by 5 p.m. submitting organization’s local time):

     Proposals Accepted Anytime

Important Information And Revision Notes

This is a new solicitation arising from a realignment of the Division of Earth Science’s disciplinary funding programs. Additional information can be found in a Dear Colleague Letter (DCL) and Frequently Asked Questions (FAQ) available on the website for the Chemical Evolution of the Solid Earth and Volcanology (CESEV).

Any proposal submitted in response to this solicitation should be submitted in accordance with the NSF Proposal & Award Policies & Procedures Guide (PAPPG) that is in effect at the time the proposal is submitted. The NSF PAPPG is regularly revised and it is the responsibility of the proposer to ensure that the proposal meets the requirements specified in this solicitation and the applicable

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U.S. National Science Foundation

Directorate for Computer and Information Science and Engineering
     Division of Computer and Network Systems
     Division of Computing and Communication Foundations
     Division of Information and Intelligent Systems
     Office of Advanced Cyberinfrastructure

Directorate for Social, Behavioral and Economic Sciences
     Division of Social and Economic Sciences
     Division of Behavioral and Cognitive Sciences

Directorate for Mathematical and Physical Sciences
     Division of Mathematical Sciences

Directorate for STEM Education
     Division of Graduate Education

Full Proposal Target Date(s):

September 29, 2025

     Last Monday in September, Annually Thereafter

January 26, 2026

     Last Monday in January, Annually Thereafter

Proposers are highly encouraged to submit by a target date. Proposals will be accepted anytime, but they may miss a particular panel or committee meeting.

Important Information And Revision Notes New focus on a complex and interdependent cyber ecosystem that involves hardware, software, networks, data, people, organizations, countries, and the physical world. Increased emphasis on (1)

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Synopsis

The Human Networks and Data Science program (HNDS) supports research that enhances understanding of human behavior by leveraging data and network science research across a broad range of topics. HNDS research will identify ways in which dynamic, distributed, or heterogeneous data can provide novel answers to fundamental questions about individual or group behavior. HNDS is especially interested in proposals that provide data-rich insights about human networks to support improved health, prosperity, and security.

HNDS has two tracks:

(1) Human Networks and Data Science – Infrastructure (HNDS-I). Infrastructure proposals will address the development of data resources and relevant analytic techniques that support fundamental Social, Behavioral and Economic (SBE) research. Successful infrastructure proposals will construct, within the financial resources provided by the award, databases or relevant analytic techniques and produce a finished product that will enable previously impossible data-intensive research in the social sciences. The

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