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Find similar grantsComputational and Data-Enabled Science and Engineering (CDS&E) is sponsored by NSF - U.S. National Science Foundation. This opportunity supports mission-aligned projects and measurable outcomes.
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Computational and Data-Enabled Science and Engineering (CDS&E) | NSF - U.S. National Science Foundation Computational and Data-Enabled Science and Engineering (CDS&E) Important information for proposers and award recipients All proposals must be submitted in accordance with the requirements specified in the funding opportunity and in the Proposal & Award Policies & Procedures Guide (PAPPG) and its supplements .
All NSF grants and cooperative agreements are subject to the applicable set of NSF award terms and conditions . NSF has updated its research security policies for NSF funded projects. Supports research that uses new computational and data science approaches to advance knowledge and accelerate discovery in science and engineering.
Supports research that uses new computational and data science approaches to advance knowledge and accelerate discovery in science and engineering. Large-scale simulations and the ability to accumulate massive amounts of data have revolutionized science and engineering.
The goal of the Computational and Data-enabled Science and Engineering (CDS&E) meta-program is to identify and capitalize on opportunities for major scientific and engineering breakthroughs through new computational and data-analysis approaches and best practices.
The CDS&E meta-program supports projects that harness computation and data to advance knowledge and accelerate discovery above and beyond the goals of the participating individual programs. The intellectual drivers may be in an individual discipline or cut across more than one discipline in various Divisions and Directorates.
A CDS&E proposal should enable and/or utilize the development and adaptation of advances in research and infrastructure in computational and data science. The CDS&E meta-program encourages research that pushes the envelope of science and engineering through computation and data, welcoming proposals in any research area supported by the participating divisions.
A proposal may address topics that develop or enable interactions among theory, computing, experiment, and observation to achieve progress on hitherto intractable science and engineering problems. Areas of emphasis for CDS&E vary by program. PIs are advised to consult the "related programs" links below before submitting.
The CDS&E meta-program is not intended to replace existing programs that support projects involving computation or the analysis of large or complex data sets using established methods. Rather, proposals submitted to the CDS&E meta-program must have a significant component of computational or data science that goes well beyond what would typically be included in these programs.
Any proposal submitted to the CDS&E program that is not responsive to this Program Description may be transferred to or reviewed within the context of an individual program. A proposal requesting consideration within the context of CDS&E should begin the title with the identifying acronym "CDS&E:". Supplement requests to existing awards may also be considered.
A CDS&E proposal should include substantive science, engineering, or computing research. Algorithm and pilot software development supporting science and engineering may also be appropriate, depending on the program. Proposers who seek to implement proven, existing methods into robust cyberinfrastructure are referred instead to the program on Cyberinfrastructure for Sustained Scientific Innovation (CSSI).
A CDS&E proposal should be submitted to one of the "Related Programs" or Divisions by the associated submission window, deadline, or target date listed in the table below. In picking the most relevant program, PIs are advised to read program descriptions and solicitations carefully and consult with cognizant Program Officers before proposal preparation.
Proposal submissions outside the receiving program's scientific scope may be transferred to a different program or returned without review.
Directorate Division and Program Submission Window or Target Date Division of Chemical, Bioengineering, Environmental, and Transport Systems September 01, 2024 - September 16, 2024 September 01- September 15, Annually Thereafter Division of Civil, Mechanical and Manufacturing Innovation September 01, 2024 - September 16, 2024 September 01- September 15, Annually Thereafter Division of Chemistry - Chemical Catalysis (CAT), Chemical Mechanism, Function, and Properties (CMFP), Chemical Synthesis (SYN) September 01, 2024 - September 30, 2024 September 01 - September 30, Annually Thereafter Division of Materials Research October 15, Annually Thereafter Division of Astronomical Sciences - Advanced Technologies and Instrumentation October 01, 2024 - November 15, 2024 October 01 - November 15, Annually Thereafter Division of Chemistry - Chemical Measurement and Imaging (CMI), Environmental Chemical Sciences (ECS), and Macromolecular, Supramolecular and Nanochemistry (MSN) October 01, 2024 - October 31, 2024 October 1 - October 31, Annually Thereafter Division of Mathematical Sciences October 15, 2024 - October 31, 2024 October 15 - October 31, Annually Thereafter Division of Astronomical Sciences - Astronomy and Astrophysics Research Grants October 01, 2024 - November 15, 2024 October 01 - November 15, Annually Thereafter Division of Physics: Investigator-Initiated Research Projects – Plasma Physics program Third Monday in November, Annually Thereafter Division of Chemistry - Chemistry of Life Processes (CLP), Chemical Structure and Dynamics (CSD), Chemical Theory, Models and Computational Methods (CTMC) Full proposals accepted anytime The CDS&E program includes participation from all Divisions within the Directorate for Mathematical and Physical Sciences (MPS) and the Division of Chemical, Bioengineering, Environmental and Transport Systems and the Division of Civil, Mechanical and Manufacturing Innovation within the Directorate for Engineering (ENG).
The appropriate contact for the CDS&E program in any Division is the Program Director for one of the participating programs in that Division, listed under "Related Programs" below.
Additional program resources ENG - Division of Chemical, Bioengineering, Environmental, and Transport Systems Programs ENG - Division of Civil, Mechanical and Manufacturing Innovation Programs Division of Mathematical Sciences: Disciplinary Research Programs Awards made through this program Browse projects funded by this program Map of recent awards made through this program MPS Astronomical Sciences Research Programs (MPS Astro) Condensed Matter and Materials Theory (CMMT) Division of Chemistry: Disciplinary Research Programs (CHE-DRP) Advanced Technologies and Instrumentation for the Astronomical Sciences (ATI) Division of Chemistry: Disciplinary Research Programs: No Deadline Pilot (CHE-DRP:NDP) Directorate for Engineering (ENG) Directorate for Mathematical and Physical Sciences (MPS)
According to the current listing, eligibility includes: All proposals must be submitted in accordance with the requirements specified in the funding opportunity. Confirm the full requirements in the official notice before applying.
Computational and Data-Enabled Science and Engineering (CDS&E) is funded by NSF - U.S. National Science Foundation. Verify program details on the funder's official page before applying.
Start from the official opportunity page linked in this listing — it carries the sponsor's submission instructions.
Materials Research Seed Grant Program (Proto-IRG Seed Grant Program) is sponsored by The Ohio State University (OSU) Institute for Materials and Manufacturing Research (IMR). This program aims to seed innovative, collaborative directions and teams in materials research at The Ohio State University, positioning OSU as a world leader in emerging fields. These teams are expected to form the basis of Interdisciplinary Research Groups (IRGs) for future NSF Materials Research Science and Engineering Center (MRSEC) competitions.
Advancing Research at the Intersection of Biology and Artificial Intelligence/Machine Learning (AI/ML) is sponsored by National Science Foundation (NSF) BIO. NSF BIO supports research combining biology and AI/ML to advance biological discovery or develop AI/ML methods inspired by biological systems, encouraging interdisciplinary collaboration. This includes research related to biomedical devices (from imaging through medical devices) and systems.
Science Granting Councils Initiative (SGCI) Multilateral Research Call is sponsored by Science Granting Councils Initiative (SGCI). This call supports multi-country research aligned with the African Union's Science, Technology and Innovation Strategy for Africa 2034 (STISA-2034). One of the five thematic streams targets Artificial Intelligence and Digital Technologies, which can include aspects of ICT infrastructure. Proposals are expected to build on existing continental efforts.
The FY2027 Defense University Research Instrumentation Program closes November 6, 2026 at 5:00 PM ET with roughly $28 million, awards from $50,000 to $3 million, and no cost-share requirement. It is down about $6 million from FY2026, it funds equipment and nothing else, and it lands ten days before the NSF MRI deadline. Here is how to split an equipment wishlist across two overlapping windows.
Read articleOn October 8, 2026 NSF's Technology, Innovation and Partnerships directorate awarded $30 million over four years to National Math Stars — fully matched by private philanthropy. A K-12 talent-identification nonprofit held the prime slot, not a university. That combination is the template, and NextGen Workforce is next.
Read articleOn October 8, 2026 NSF named the founding partners of the X-Labs Consortium — Astera, Ginkgo Bioworks, the Sloan Foundation, the Secunda Family Foundation, Occam Foundry, and the Florida Quantum Center — representing over $300 million in commitments. For a program that funds teams with no institutional home, the facilities layer changes what a credible Phase 0 proposal looks like.
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