Important information about NSF’s implementation of the revised 2 CFR

NSF Financial Assistance awards (grants and cooperative agreements) made on or after October 1, 2024, will be subject to the applicable set of award conditions, dated October 1, 2024, available on the NSF website. These terms and conditions are consistent with the revised guidance specified in the OMB Guidance for Federal Financial Assistance published in the Federal Register on April 22, 2024.

Important information for proposers

All proposals must be submitted in accordance with the requirements specified in this funding opportunity and in the NSF Proposal & Award Policies & Procedures Guide (PAPPG) that is in effect for the relevant due date to which the proposal is being submitted. It is the responsibility of the proposer to ensure that the proposal meets these requirements. Submitting a proposal prior to a specified deadline does not negate this requirement.

Dear Colleague Letter

NSF-Italian Ministry of Universities and Research Lead Agency Opportunity on Artificial Intelligence

Encourages U.S.–Italy collaborative research proposals for research in the area of artificial intelligence.

Encourages U.S.–Italy collaborative research proposals for research in the area of artificial intelligence.

Dear Colleague:

The U.S. National Science Foundation (NSF) and the Ministry of Universities and Research of the Italian Republic (MUR) have signed a Memorandum of Understanding (MOU) Concerning Artificial Intelligence Collaboration. The MOU provides the framework to encourage collaboration between the U.S. and Italy research communities and sets out the principles by which jointly supported activities might be developed. The MOU provides for an international collaboration arrangement whereby U.S. researchers may receive funding from NSF and Italian researchers may receive funding from MUR. Through a "Lead Agency Opportunity," NSF and MUR will allow proposers from both countries to submit a single collaborative proposal that will undergo a single review process at NSF.

This document provides guidelines for the preparation, submission, review, and award of joint NSF-MUR artificial intelligence proposals.

Collaborative research proposals will be accepted to the Small project class of the CISE Core Programs, available at https://new.nsf.gov/funding/opportunities/computer-information-science-engineering-core. Italian researchers are invited to read MUR funding rules at http://www.ricercainternazionale.miur.it/accordi/accordi-bilaterali/italia-usa.aspx. Limits for U.S. researchers on the number of proposal submissions are described in the relevant CISE Core Programs solicitation referenced.

Proposers should review the NSF CISE and MUR programs for further information on what areas of research may be eligible for support through this activity. Following the policies for the NSF and MUR programs from which funding is sought, proposals should adhere to the description of Small Projects accommodating up to $600,000 in budget on the U.S. side and up to €500,000 in budget on the Italian side, with durations up to three years. Proposers are strongly encouraged to contact cognizant Program Directors to ensure the proposal aligns with the goals and requirements of the program prior to submission.

Proposers are advised that all documents submitted to NSF or MUR may be shared by secure electronic means among the participating NSF and MUR units to implement the Lead Agency Opportunity.

Proposal Preparation and Submission

All proposals must fall within the mission and funding parameters of NSF and MUR. Proposals that do not fall within the missions of both funding organizations will not be considered.

Full Proposal Submission

The eligibility to submit a proposal follows the policies for the NSF and MUR programs respectively.

  • Proposers should follow all requirements outlined in this DCL as well as the guidance contained in the CISE Core Programs solicitation. The proposal should describe the research activities of both the U.S. and Italian partners.  
  • As specified in the relevant program solicitation, proposers are to comply with the proposal preparation requirements outlined in NSF's Proposal and Award Policies and Procedure Guide (PAPPG – https://www.nsf.gov/publications/pub_summ.jsp?ods_key=pappg) and submit the proposal through Research.gov (https://www.research.gov/research-web/) or Grants.gov (http://grants.gov).
  • By submitting, PIs and their organizations agree that NSF may share proposals, unattributed reviews and information pertaining to the review process with MUR.
  • Proposals submitted to the Small Project Class are accepted at anytime; however, within a week after submission to NSF CISE’s Core Program, the proposal should be submitted to MUR via the web platform https://banditransnazionali-miur.cineca.it. The submission to MUR should contain the mandatory administrative and financial information required by MUR funding rules, published on the Italian submission platform and the Ministry web site, the proposal submitted to NSF, and the proposal number issued by NSF (this information is required for matching the proposals). 
  • The title of the proposal should start with "NSF-MUR:” after any solicitation specific title requirements.
  • The proposal should describe the full proposed research program, including the total U.S. and Italian resources that will be part of the project. The Project Summary and Project Description must include a description of the collaboration, including an explanation of the role(s) of the Italian collaborator(s) and an explanation of how the team will work together.
  • The proposal must describe the intellectual merit of the proposed research, including the value of the international collaboration, and the anticipated broader impacts of the effort.
  • The proposal should indicate only the U.S. expenses on the NSF Budget Form. A detailed breakdown of funding requested from MUR should be included in the proposal as a Supplementary Document. Proposals that request duplicative funding from NSF and MUR will be returned without review. The Budget Justification section of the proposal should address the full project budget (that is, both the NSF and MUR funding items). 
  • A post-doctoral mentoring plan is not needed if funding for postdocs is requested only from MUR. Including one, however, is allowed.  
  • Italian personnel should be listed in the Overview section of the Project Summary as "non-NSF funded collaborators." This listing is for administrative purposes and is not intended to characterize the level or value of the contribution of Italy personnel to the project. Guidance on information to provide for "non-NSF funded collaborators" is below:
  • Biographical Sketch – Required. The biographical information must be clearly identified as "non-NSF funded collaborators" biographical information and uploaded as a single PDF file in the Other Supplementary Documents section of the proposal. Use of a specific format is not required.
  • Collaborators and Other Affiliations (COA) Information – Optional but requested. The COA information should be provided through the use of the COA template, identified as "non-NSF funded collaborators" COA information, and uploaded as a PDF file in the Single Copy Documents section of the proposal.
  • Current and Pending Support is not required for the Italian personnel.
  • Results of Prior Research is not required for the Italian personnel.

Additional Documents

Proposers should provide all the documentation outlined in this DCL as well as the documents required by the CISE Core Programs solicitation.

Merit Review

Proposals under this Lead Agency Opportunity will be reviewed alongside all other unsolicited or standard research grant proposals received in the same funding round or call and will not undergo a special or separate review process. Proposals will be evaluated in accordance with the NSF's merit review criteria.

Funding Decisions

NSF, as the lead agency, will use its usual internal procedures to determine whether a proposal will be awarded or declined. All potential award decisions will be discussed with MUR. The number of U.S.-Italy projects selected for funding and the total amount to be allocated will depend on the number and quality of the submitted projects and the available funding for each funding agency.

NSF will advise all proposers whether their proposal has been recommended for funding or will be declined. Proposers will receive copies of the reviewers' unattributed comments and, where applicable, a panel summary.

NSF and MUR will coordinate award timing as much as possible, but because of different funding cycles, it is possible that some projects will have delayed start dates to wait until funds become available or until all pre-award requirements are met. Wherever possible, NSF and MUR will endeavor to hold standard turnaround times for each participating agency. In exceptional circumstances outcomes could be delayed.

Should a proposal be declined for funding, proposers should refer to both NSF and MUR resubmission guidelines.

Post Award Considerations

Recipients are expected to comply with the award conditions and reporting requirements of the agency from which they receive funding.

Recipients are required to acknowledge NSF and MUR in any reports or publications arising from the grant.

NSF and MUR will consider requests for extensions using standard procedures.

All NSF and MUR requirements for data storage are applicable to investigators funded by their respective agencies.

Data Protection Considerations

Data are expected to be securely shared between NSF and MUR to enable the secure and efficient processing of full proposals for the NSF-MUR funding opportunity. Data shared may include anonymized reviews and panel summaries. NSF and MUR are committed to maintaining data confidentiality, protection, and privacy and intend to fully abide by their own applicable laws and policies concerning the sharing of data in collaborative activities.

Questions about this DCL may be directed to nsf-mur-ai@nsf.gov.

Sincerely,

Dilma Da Silva 
Assistant Director (Acting), Directorate for Computer and Information Science and Engineering