Physical Sciences & Engineering

 Limit: 1 // J. Denno (Cyber Convergence Center) 

NCAE-Cs may submit one proposal which provides a response to one or two focus areas identified below. The total proposal submission per NCAE-C may not exceed $250,000.00 ($125,000.00 for each project). Any proposals exceeding this limit will automatically be rejected. 

 Universities designated under the National Centers of Academic Excellence in Cybersecurity (NCAE-C)  which includes  National Centers of Academic Excellence in Cyber Defense Education and  National Centers of Academic Excellence – Research,  and  National Centers of Academic Excellence – Cyber Operations  (hereinafter referred to as NCAE-Cs) 

The Department of Defense (DoD) Cyber Scholarship Program (CySP) is authorized by Chapter 112 of title 10, United States Code, Section 2200. The purpose of the program is to support the recruitment of new cyber talent and the retention of current highly skilled professionals within the DoD cyber workforce. Additionally, this program serves to enhance the national pipeline for the development of cyber personnel by providing grants to institutions of higher education. The DoD Cyber and Digital Services Academy (DCDSA) will partner with the DoD CySP/DCDSA in 2024. 

Regionally and nationally accredited U.S. institutions of higher education, designated under the National Centers of Academic Excellence in Cybersecurity (NCAE-C) and known as National Centers of Academic Excellence in Cyber Defense, Research, and/or Cyber Operations (hereinafter referred to as NCAE-Cs) are invited to submit proposals for developing and managing a full-time, institution-based, grant-funded scholarship program in cyber-related disciplines for Academic Year 2024- 2025. NCAE-Cs may propose collaboration with other accredited institutions, and are encouraged to include accredited post-secondary minority institutions. NCAE-Cs must be in good standing with the NCAE-C Program Office and not be delinquent on any required documentation by the NCAE-C Program Office. 

Consistent with 10 U.S.C. 2200b, NCAE-C proposals to this solicitation may also request modest collateral support for purposes of institutional capacity building to include faculty development, laboratory improvements, and/or curriculum development, in cyber-related topics to providing a strong foundation for a DoD CySP/DCDSA/DCDSA. [Special note: Requirements for proposing modest capacity building support are detailed in ANNEX II.] 

To continue the development of a strong foundation for recruitment scholarship program during the Academic Year 2024-2025, students falling into one of the following categories may apply: 

• • Rising second-year NCAE-C Community College students who will be transitioning into a bachelor’s degree program at a 4-year NCAE-C 
• • Current individuals who hold a non-cyber related bachelor’s or graduate degree, cross training into cyber by pursuing an associate’s degree. 
• • Juniors or Seniors pursuing a bachelor's degree (Sophomore's promoting to a Junior in Fall 2024 are eligible to apply) 
• • Students in their first or second year of a master's degree; or 
• • Students pursuing doctoral degrees. 

Traditional National Guardsmen and reservists are eligible to apply under the recruitment program. Current DoD civilians and active duty military members are only eligible for the retention program. Applications for the retention program are processed under a different memorandum. NCAE-C are not required to forward or handle retention student applications. These individuals may also participate in the retention community college program. 

Reserve Officer’s Training Corps (ROTC) participants are eligible to apply as long as they do not currently have a service obligation with their ROTC activities. 

Employees of non-DoD federal agencies are ineligible for either program. 

No Applicants // Limit: 2 // Tickets Available: 2 

An applicant/institution may submit no more than two (2) applications in response to this announcement.

The U.S. Nuclear Regulatory Commission (NRC) is an independent agency, established by the Atomic Energy Act of 1954, as amended, tasked with licensing, and regulating the Nation’s civilian use of byproduct, source, and special nuclear material to ensure adequate protection of public health and safety, to promote the common defense and security, and to protect the environment.

The program provides funding to support research and development (R&D) for nuclear science, engineering, technology, and related disciplines to develop a workforce capable of supporting the design, construction, operation, and regulation of nuclear facilities and the safe handling of nuclear materials. University R&D activities provide an opportunity to complement current, ongoing NRC-led research.

More specifically, the program shall be used to provide financial assistance for R&D projects relevant to the programmatic mission of the NRC referenced above, with an emphasis on providing financial assistance with respect to research, development, demonstration, and commercial application of new and advanced nuclear technologies. New this year, nontechnical research will be considered under this announcement (for example, projects that would foster the development of innovative community engagement strategies, including incorporation of principles of equity and environmental justice).

Award of these grants is contingent upon the availability of funds. The estimated budget for this program is $6,000,000.00. The NRC anticipates that there maybe up to twelve (12) grants awarded as a result of this NOFO. The number of awards depends on the number, quality, duration, and costs of the applications received.

This is a three (3)-year program. Research and development funds may be requested up to $500,000.00 total costs (direct costs and facilities and administrative costs) for the project period.

 Limit: 15* // Tickets Available: 10

PO Confirmed DOE will accept 15 applications, 3 for each of the 5 research areas.

L. Xuan ( Computer science) - Research Area 2: AI Innovations for Scientific Knowledge Synthesis and Software Development
M. Chertkov (Pharmacy) - Research area 3: AI Innovations for Computational Decision Support of Complex Systems. 
R. Tandon (Electrical & Computer Engineering) // Subaward Lawrence Berkeley National Lab - Research Area 4: Federated and privacy-preserving for foundation and other AI models for science.
S. Salehi (Electrical and Computer Engineering) - Research Area 5: The Co-Design of Energy-Efficient AI Algorithms and Hardware Architectures. 
M. Krunz (Electrical & Computer Engineering) -  Research Area 5: The Co-Design of Energy-Efficient AI Algorithms and Hardware Architectures.
T. Adegbija (Electrical & Computer Engineering) -  Research Area 5: The Co-Design of Energy-Efficient AI Algorithms and Hardware Architectures.

The DOE SC program in Advanced Scientific Computing Research (ASCR) hereby announces its interest in basic computer science and applied mathematics research in the fundamentals of Artificial Intelligence (AI) for science. Specifically, advancements in this area are sought that can enable the development of: 

• Foundation models for computational science;
• Automated scientific workflows and laboratories;
• Scientific programming and scientific-knowledge-management systems;
• Federated and privacy-preserving training for foundation and other AI models for science; and
• Energy-efficient AI algorithms and hardware for science.

Limit: 1 // G. Yong (Eller College of Managemen)

Limit on Number of Proposals per Organization: An organization may submit one proposal per submission window. An organization must wait for a determination from NSF (e.g., Award, Decline, or Returned Without Review) on the pending proposal before submitting a new proposal in the next window. Declined proposals require a new invitation to submit (via the Concept Outline process) and significant revision, while proposals Returned Without Review may be submitted using the same invited Concept Outline (assuming that the proposal is received within one year of the original Concept Outline invitation).

The National Science Foundation and its partners support the continued growth of a broad and diverse interdisciplinary research community for the advancement of Artificial Intelligence (AI) and AI-powered innovation, providing a unique opportunity to broadly promote the NSF vision and core values, especially inclusion and collaboration. The National Artificial Intelligence Research Institutes program has established a national network of multisector flagship centers of AI research and workforce development that address a wide range of society's grand challenges through AI-powered innovation.

PROGRAM TRACKS

This program solicitation offers two Tracks corresponding to stages of readiness for partnerships in AI Institutes. These are “ExpandAI Capacity Building Pilots” and “ExpandAI Partnerships” as described below.

Track 1: ExpandAI Capacity Building Pilots

Capacity Building Pilots (CAP) are planning and growth efforts focused on the establishment of AI activities at the funded MSI and the early exploration of future synergistic partnerships that have the potential to be part of prospective ExpandAI Partnerships. Successful pilots will result in establishing new AI research capacity, education/workforce development in AI, and/or AI infrastructure capacity at the proposing institution and, potentially, a basis for future AI partnerships. CAP activities should plan for engaging appropriate communities to test the feasibility of partnerships as well as developing plans for continuing capacity development. Plans should consider required research infrastructure, plans to leverage established groups in related research areas, and inclusion of faculty training and research experiences that emphasize the diversification of investigators. 

Proposals must articulate a clear vision motivating the capacity building activities, with a focus on long-term benefits to the MSI such as enhanced faculty capacity for foundational and/or use-inspired AI research or new effective models for increased education and career pathways in AI. Proposals to this track must include a strong Institutional Need and Support Statement (see proposal preparation instructions) containing an assessment of the current AI research and instructional capacity and infrastructure, a demonstration of institutional need for capacity building in AI, and a statement of the commitment of institutional support for the proposed activities. Proposals that substantiate a strong case in this need and support statement are likely to be most compelling for the funding opportunity. Further guidance for this supporting document can be found in Proposal Preparation Instructions.

Successful proposals will feature a Capacity Building Plan that features clear and measurable outcomes/benefits of capacity building. Suitable activities for such a plan are:

• establishment or significant enhancement of foundational or use-inspired AI research, marked by increased faculty research output;
• design of academic pathways or innovative models for teaching and learning in AI, incorporating how students learn effectively in AI activities, and bringing AI disciplinary advances into the undergraduate and graduate experience;
• establishment or significant expansion of AI career pathways for students resulting from new AI activities;
• enhanced AI research infrastructure;
• significant increase in the participation of investigators and students who have been traditionally underserved and underrepresented in AI; and
• a plan for objective process evaluation in support of the proposed efforts.

Note that this list is representative of suitable activities and outcomes for this track. CAP activities need not be limited to this list, and proposals do not have to include every type of outcome represented in that list. Proposers are encouraged to select and integrate the activities most appropriate for their institutional context and their vision for capacity building toward partnerships. 

Early partnership development between the proposing MSI and one or more AI Institutes is neither required nor encouraged in a CAP proposal.

Track 2: ExpandAI Partnerships

The ExpandAI Partnership (PARTNER) track is an opportunity for MSIs to scale up already-established AI research and/or education programs and to initiate/leverage new collaborations with AI Institutes. These partnerships will be multi-organization collaborations submitted by an MSI and will include a subaward to an AI Institute. PARTNER projects are centered around shared, complementary goals. Proposals will be submitted as single-organizational collaborative proposals. PARTNER proposals may only be submitted by a qualifying MSI as indicated in Eligible Institutions in this solicitation. 

PARTNER proposals should scale up and make fully productive an appropriate existing capacity in AI research, education/workforce development, and/or infrastructure capacity. The proposing MSI in this track is not required to have previously been awarded a CAP project under this program. PARTNER proposals must constitute a significant new partnership that has the clear potential to build on the institution’s current AI capacity as well as leverage the intrinsic strengths and talents of the MSI for mutual benefit in collaborative AI activities.

MSIs applying for this track must demonstrate readiness to leverage external expertise and financial resources to focus on medium- and long-range plans to leverage this funding opportunity and new partnerships to develop AI capacity within the MSI, including but not limited to further development of the MSI’s envisioned methodological thrusts, use cases, educational and/or workforce development activities, and the potential for the MSI to expand and scale these efforts through formal, mutually beneficial partnerships. Proposals should include at least one (and if appropriate, more) established AI Institutes in developing a roadmap for collaborative work in some unifying theme or focus. 

PARTNER proposals must feature a compelling Partnership Roadmap for collaborative work in some unifying theme or focus. Roadmaps are the beginning of a joint strategy between organizations for collaborative work. These roadmaps may also include community building activities (e.g., workshops) to further develop common interests, objectives, and goals for the growth of collaborative activities. Effective roadmaps are both depicted visually (e.g., conceptual diagram, logic model, table, etc.) and fully explained by a descriptive narrative. The roadmap should address all proposed projects involving research, education/workforce development, infrastructure, and any other types that are applicable to the collaboration. Roadmaps might address:

• enhancement of existing projects by virtue of new collaboration;
• initiation of new projects made possible by the collaboration;
• community building activities (e.g., workshops) to further develop common interests, objectives, and further growth of the partnership;
• potential and plans for scaling nascent programs;
• an evaluation plan for measuring the growth and mutual benefit of activities in all projects.

No Applicants /// Limit: 1 // Tickets Available: 0

There won't be a submission for this program during the June deadline. 

Limit on Number of Proposals per Organization: An organization may submit one proposal per submission window. An organization must wait for a determination from NSF (e.g., Award, Decline, or Returned Without Review) on the pending proposal before submitting a new proposal in the next window. Declined proposals require a new invitation to submit (via the Concept Outline process) and significant revision, while proposals Returned Without Review may be submitted using the same invited Concept Outline (assuming that the proposal is received within one year of the original Concept Outline invitation).

The National Science Foundation and its partners support the continued growth of a broad and diverse interdisciplinary research community for the advancement of Artificial Intelligence (AI) and AI-powered innovation, providing a unique opportunity to broadly promote the NSF vision and core values, especially inclusion and collaboration. The National Artificial Intelligence Research Institutes program has established a national network of multisector flagship centers of AI research and workforce development that address a wide range of society's grand challenges through AI-powered innovation.

PROGRAM TRACKS

This program solicitation offers two Tracks corresponding to stages of readiness for partnerships in AI Institutes. These are “ExpandAI Capacity Building Pilots” and “ExpandAI Partnerships” as described below.

Track 1: ExpandAI Capacity Building Pilots

Capacity Building Pilots (CAP) are planning and growth efforts focused on the establishment of AI activities at the funded MSI and the early exploration of future synergistic partnerships that have the potential to be part of prospective ExpandAI Partnerships. Successful pilots will result in establishing new AI research capacity, education/workforce development in AI, and/or AI infrastructure capacity at the proposing institution and, potentially, a basis for future AI partnerships. CAP activities should plan for engaging appropriate communities to test the feasibility of partnerships as well as developing plans for continuing capacity development. Plans should consider required research infrastructure, plans to leverage established groups in related research areas, and inclusion of faculty training and research experiences that emphasize the diversification of investigators. 

Proposals must articulate a clear vision motivating the capacity building activities, with a focus on long-term benefits to the MSI such as enhanced faculty capacity for foundational and/or use-inspired AI research or new effective models for increased education and career pathways in AI. Proposals to this track must include a strong Institutional Need and Support Statement (see proposal preparation instructions) containing an assessment of the current AI research and instructional capacity and infrastructure, a demonstration of institutional need for capacity building in AI, and a statement of the commitment of institutional support for the proposed activities. Proposals that substantiate a strong case in this need and support statement are likely to be most compelling for the funding opportunity. Further guidance for this supporting document can be found in Proposal Preparation Instructions.

Successful proposals will feature a Capacity Building Plan that features clear and measurable outcomes/benefits of capacity building. Suitable activities for such a plan are:

• establishment or significant enhancement of foundational or use-inspired AI research, marked by increased faculty research output;
• design of academic pathways or innovative models for teaching and learning in AI, incorporating how students learn effectively in AI activities, and bringing AI disciplinary advances into the undergraduate and graduate experience;
• establishment or significant expansion of AI career pathways for students resulting from new AI activities;
• enhanced AI research infrastructure;
• significant increase in the participation of investigators and students who have been traditionally underserved and underrepresented in AI; and
• a plan for objective process evaluation in support of the proposed efforts.

Note that this list is representative of suitable activities and outcomes for this track. CAP activities need not be limited to this list, and proposals do not have to include every type of outcome represented in that list. Proposers are encouraged to select and integrate the activities most appropriate for their institutional context and their vision for capacity building toward partnerships. 

Early partnership development between the proposing MSI and one or more AI Institutes is neither required nor encouraged in a CAP proposal.

Track 2: ExpandAI Partnerships

The ExpandAI Partnership (PARTNER) track is an opportunity for MSIs to scale up already-established AI research and/or education programs and to initiate/leverage new collaborations with AI Institutes. These partnerships will be multi-organization collaborations submitted by an MSI and will include a subaward to an AI Institute. PARTNER projects are centered around shared, complementary goals. Proposals will be submitted as single-organizational collaborative proposals. PARTNER proposals may only be submitted by a qualifying MSI as indicated in Eligible Institutions in this solicitation. 

PARTNER proposals should scale up and make fully productive an appropriate existing capacity in AI research, education/workforce development, and/or infrastructure capacity. The proposing MSI in this track is not required to have previously been awarded a CAP project under this program. PARTNER proposals must constitute a significant new partnership that has the clear potential to build on the institution’s current AI capacity as well as leverage the intrinsic strengths and talents of the MSI for mutual benefit in collaborative AI activities.

MSIs applying for this track must demonstrate readiness to leverage external expertise and financial resources to focus on medium- and long-range plans to leverage this funding opportunity and new partnerships to develop AI capacity within the MSI, including but not limited to further development of the MSI’s envisioned methodological thrusts, use cases, educational and/or workforce development activities, and the potential for the MSI to expand and scale these efforts through formal, mutually beneficial partnerships. Proposals should include at least one (and if appropriate, more) established AI Institutes in developing a roadmap for collaborative work in some unifying theme or focus. 

PARTNER proposals must feature a compelling Partnership Roadmap for collaborative work in some unifying theme or focus. Roadmaps are the beginning of a joint strategy between organizations for collaborative work. These roadmaps may also include community building activities (e.g., workshops) to further develop common interests, objectives, and goals for the growth of collaborative activities. Effective roadmaps are both depicted visually (e.g., conceptual diagram, logic model, table, etc.) and fully explained by a descriptive narrative. The roadmap should address all proposed projects involving research, education/workforce development, infrastructure, and any other types that are applicable to the collaboration. Roadmaps might address:

• enhancement of existing projects by virtue of new collaboration;
• initiation of new projects made possible by the collaboration;
• community building activities (e.g., workshops) to further develop common interests, objectives, and further growth of the partnership;
• potential and plans for scaling nascent programs;
• an evaluation plan for measuring the growth and mutual benefit of activities in all projects.

Limit: 3 // Tickets Available: 2

N. Rengaswamy (Electrical and Computer Engineering)

The DOE SC program in Advanced Scientific Computing Research (ASCR) announces its interest in receiving applications that advance the field of quantum computing by developing enabling end-to-end software infrastructures. This FOA solicits applications from large cross- disciplinary teams that will advance computer science toward a software stack that is ready to leverage multiple quantum technologies, or will develop mathematical foundations, algorithms, and software tools toward quantum utility [1] demonstration for applications within the DOE mission.

Research proposed in response to this FOA must primarily focus on addressing one of the two topics described below:

Topic 1 – Modular Software Stack: The diversity of quantum computing architectures and hardware technologies is expected to persist into the foreseeable future; this is an important consideration that guides the advancement of computer science sought in this topic. The development of an integrated computational ecosystem requires a general-purpose quantum software stack that is adaptable to, and takes advantage of, multiple kinds of quantum hardware. We seek basic research in computer science and applied mathematics that:

• Addresses practical and fundamental bottlenecks that hinder modularity and potential synergy among selected hardware technologies;
• Pursues general approaches to integration that may remain relevant for future technologies;
• Devises ways to embed quantum processors in parallel and distributed computing models; and
• Integrates error management across the software stack.

Topic 2 – Quantum Utility: This topic aims to advance the research towards achievement and demonstration of quantum utility [1] by developing new algorithms and fine-tuning all levels of the software stack for a selected portfolio of promising problems within the ASCR mission.

Applications should:

• Choose generalizable application-inspired target problems;
• Develop algorithms for optimized math kernels and math primitives for selected current (NISQ) and future quantum systems that significantly advance state-of-the-art performance for the selected target problems;
• Adapt, if needed, any level of the software stack for the specific target problems; and
• Estimate quantum resources by employing important complementary metrics, including energy-to-solution.

Verification protocols and tools are important for both Topic 1 and Topic 2 and should be discussed in the application.Applicants must choose and specify Topic 1 or Topic 2 as the focus of their application. In the choice of Topic 1 or 2, proposed research is encouraged to consider multiple metrics, such as qubit count, gate fidelity, and qubit connectivity.

The ceiling and floor specified below are for total costs, both direct and indirect costs.

Ceiling

$3,000,000 per year

Applications requesting more than this amount of support may be declined without further review.

Floor

$250,000 per year

Applications requesting less than this amount of support may be declined without further review.

Submit ticket request  // Limit: 1 // Tickets Available: 1 

The NSF ADVANCE program goal is to broaden the implementation of evidence-based systemic change strategies that promote equity for STEM faculty in academic workplaces and the academic profession. The NSF ADVANCE program provides grants to enhance the systemic factors that support equity and inclusion and to mitigate the systemic factors that create inequities in the academic profession and workplaces. Systemic (or organizational) inequities may exist in areas such as policy and practice as well as in organizational culture and climate. UArizona is only elegible for the Partnership Track.

• Partnership projects are expected to result in national or regional transformation in STEM academic workplaces and the academic profession and demonstrate significant reach. Partnership projects can focus on the transformation of institutions and organizations and/or the transformation within one or more STEM disciplines.

Submit ticket request  // Limit: 1 // Tickets Available: 1 

The intent of this solicitation is to request proposals from organizations who are willing to serve as resource providers within the NSF Advanced Computing Systems and Services (ACSS) program. Resource providers would (1) provide advanced cyberinfrastructure (CI) resources in production operations to support the full range of computational- and data-intensive research across all of science and engineering (S&E), and (2) ensure democratized and equitable access to the proposed resources. The current solicitation is intended to complement previous NSF investments in advanced computational infrastructure by provisioning resources, broadly defined in this solicitation to include systems and/or services.

• Category I, Capacity Resources: production computational resources maximizing the capacity provided to support the broad range of computation and data analytics needs in S&E research.

 Limit: 5* // Tickets Available: 4

Q. Hoa ( Aerospace-Mechanical Engineering) -  Topic 2. Smart Manufacturing Platforms for Battery Production.

The goals of this FOA are to advance manufacturing platform technologies in the following specific areas: 1) Platforms for next generation battery manufacturing - focusing on manufacturability and scalability of critical battery components and system architectures 2) Smart manufacturing platforms for battery production - developing innovative ways to revolutionize battery prouction. *An entity may submit only one Concept Paper for each topic area/sub-topic area.
 

Topics include:

1. Platforms for Next Generation Battery Manufacturing

     1.1 Processes and Machines for Sodium-ion Batteries

     1.2 Processes and Design for Manufacturability of Flow Batteries

     1.3 Scalable Manufacturing of Nanolayered Films for Energy Storage

2. Smart Manufacturing Platforms for Battery Production

No Applicants  //  Limit: 1 // Tickets Available: 1 

Up to one (1) QSTD Pilot proposal may be submitted per Lead Organization.

NSF support for use-inspired and translational research in Quantum Information Science and Engineering (QISE), combined with its existing strength in support of the underlying foundational research, is anticipated to accelerate development of a market for quantum technologies.The NQVL aims to develop and utilize use-inspired and application-oriented quantum technologies. In the process, NQVL researchers will explore quantum frontiers, foster QISE workforce education and training, engage in outreach activities at all levels, and promote broadening participation, diversity, equity, and inclusion in QISE, thereby lowering barriers at all entry points of the research enterprise. 

It is required that prospective PIs contact the NQVL Program Officer as soon as possible, but not later than two weeks before submitting a proposal in response to this solicitation, to ascertain that the focus and budget of their proposal is appropriate for this solicitation.