Mathematics, Computational, & Data Sciences

1. A.  Jalilzadeh (Systems and Industrial Engineering)
2. M. Chertkov (Applied Mathematics)
3. S. Missoum ( Aerospace and Mechanical Engineering)

4. D. Moore (Natural Resources & the Environment)

UA may submit four pre-applications as the lead institution in a single- or multi-institutional team. No more than two pre-applications for each PI at the applicant institution are allowed. 

The DOE SC program in Advanced Scientific Computing Research (ASCR) hereby announces its interest in research applications to explore potentially high-impact approaches in the development and use of scientific machine learning (SciML) and artificial intelligence (AI) in the predictive modeling, simulation and analysis of complex systems and processes.

High-performance computational models, simulations, algorithms, data from experiments and observations, and automation are being used to accelerate scientific discovery and innovation. Recent workshops, report, and strategic plans across the DOE have highlighted the research, development, and use of artificial intelligence and machine learning for science, energy, and security. Relevant domains include materials, environmental, and life sciences; high-energy, nuclear, and plasma physics; and the DOE Energy Earthshots Initiative, for examples. A 2018 Basic Research Needs workshop and report on scientific machine learning (SciML) and AI1 identified six Priority Research Directions (PRDs) for the development of the broad foundations and research capabilities needed to address such DOE mission priorities. The first three PRDs for foundational research are a set of themes common to all SciML approaches and correspond to the need for domain-awareness, interpretability, and robustness and scalability, respectively. Of the other three PRDs for capability research, PRD #5 (Machine Learning-Enhanced Modeling and Simulation) and uncertainty quantification are the subject of this FOA. 

No applicants // Limit: 3 // Tickets Available: 3

UA  is limited to no more than three pre-applications, or applications with one for each PI at the applicant institution.

The DOE SC program in Fusion Energy Sciences (FES) hereby announces its interest in applications in the areas of Machine Learning (ML), Artificial Intelligence (AI), and Data Resources for fusion energy and plasma sciences. The goal of this FOA is to support multidisciplinary teams aiming to apply advanced and autonomous algorithms to address high-priority research opportunities across the FES program. Applicants are encouraged to propose research in new systems for managing, formatting, curating, and accessing experimental and simulation data, provided in publicly available databases. Of high programmatic importance are approaches that support the realization of a fusion pilot plant on a decadal timescale.

No applicants // Limit: 2 // Tickets Available: 2 

AU is limited to both: • No more than two pre-applications or applications as the lead institution. • No more than one pre-application or application for each PI.

The DOE SC program in Advanced Scientific Computing Research (ASCR) hereby announces its interest in receiving applications focusing on basic research in computer science that explores innovative approaches to creating distributed resilient systems for science. Such systems might be national or global in scale, linking geographically-distributed computing systems and scientific instruments, and might involve a large number of edge devices or sensors, but regardless, must manage computation and data in scalable and fault-tolerant manner. Important research challenges involve techniques for advanced middleware and operating and runtime systems, with this FOA targeting two research areas: 1) scalable system modeling, and 2) adaptive management and partitioning of resources. Advances in these areas will contribute to scaling-up our increasingly complex and interconnected scientific enterprise.

No applicants // Limit: 1 // Tickets Available: 1 

Through this solicitation, NSF seeks to foster a network of S-STEM stakeholders and further develop the infrastructure needed to generate and disseminate new knowledge, successful practices and effective design principles arising from NSF S-STEM projects nationwide. The ultimate vision of the legislation governing the S-STEM parent program[1] (and of the current S-STEM-Net solicitation) is that all Americans, regardless of economic status, should be able to contribute to the American innovation economy if they so desire.

To support collaboration within the S-STEM network, NSF will fund several S-STEM Research Hubs (S-STEM-Hub). The S-STEM Network (S-STEM-Net) will collaborate to create synergies and sustain a robust national ecosystem consisting of multi-sector partners supporting domestic low-income STEM students in achieving their career goals, while also ensuring access, inclusion, and adaptability to changing learning needs. The Hubs will investigate evolving barriers to the success of this student population. It will also disseminate the context and circumstances by which interventions and practices that support graduation of domestic low-income students (both undergraduate and graduate) pursuing careers in STEM are successful.

The target audience for this dissemination effort is the community of higher education institutions, faculty, scholars, researchers and evaluators, local and regional organizations, industry, and other nonprofit, federal, state, and local agencies concerned with the success of domestic low-income STEM students in the United States.

UArizona may submit one proposal as the lead organization for a Partnership Track. 
UArizona is not eligible for an IT, adaptation, or catalyst grant because of previous funding for an ADVANCE IT grant.

Due dates (all LOIs are accepted and can submit full proposal):

• LOI: 07/08/2023
• Full Proposal:11/01/2023
   

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.

Partnership Track 

The Partnership* track supports projects designed to result in the regional or national diffusion and/or scale-up of evidence-based systemic change strategies. Partnership projects are expected to involve two or more partners. Partnership projects must be designed to have a significant reach to individuals and/or organizations with evidence-based systemic change strategies to enhance equity for STEM faculty in academic workplaces and the academic profession. Individuals and organizations may include, but are not limited to, academic administrators, academic staff in relevant positions (such as human resource officers, institutional research directors, equal opportunity officers, and Title VII and Title IX officers), STEM faculty and leaders, editors and publishers, STEM professional societies, non-profit institutions of higher education, and STEM research funders. The proposer(s) must explain the significance of the reach in the proposal. Describe the intended reach of the project in numbers and percentages as well as the impact of the project in terms of the expected systemic, cultural and/or climatic change. This will be different depending on the systemic inequity issues that are being addressed, the population(s) of interest, and the proposed strategies.

*Opportunity for ADVANCE Adaptation and Partnership Proposers to Collaborate with other Projects Initiated with NSF Funds

ADVANCE Adaptation and Partnership projects are encouraged to propose a mutually beneficial collaboration with one or more projects initiated with NSF funds (NSF-initiated projects). These NSF-initiated projects can be within or outside the institution(s) participating in the proposed ADVANCE project and must fall into one of the following categories:

• Systemic and institutional transformation projects: the institutional change track in the Alliances for Graduate Education and the Professoriate (AGEP) and the Institutional and Community Transformation track in the Improving Undergraduate STEM Education (IUSE): EDU programs.
• NSF INCLUDES National Network: The NSF INCLUDES National Network includes the Coordination Hub, Alliances, Design and Development Launch Pilots, planning grants, and conference projects.
• STEM graduate education projects: such as Alliances for Graduate Education and the Professoriate (AGEP), Innovations in Graduate Education (IGE), CyberCorps (R): Scholarship for Service (SFS), and National Science Foundation Research Traineeship (NRT).

ADVANCE Adaptation and Partnership projects that propose a collaboration may request up to an additional $250,000 over the life of the project. The additional funds are intended to support additional work to align systemic change and institutional transformation efforts particularly those impacting STEM faculty and to share equity and intersectional perspectives with other NSF projects. The funds are not intended for direct support to students, postdoctoral trainees, or faculty to do their STEM research or educational programs. The additional funds could cover costs such as travel and staff time, implementing collaborative activities, and the participation of additional individuals in ADVANCE project activities or the activities of the partner. NSF-initiated projects eligible for collaboration must be on-going: either currently funded by NSF or sustained with non-NSF funds. Letter(s) of collaboration from the NSF-initiated project representative(s) should be included in the supplementary documents.

CK. Chan (Astronomy) - Track 1: ExpandAI Capacity Building Pilots.

Eligible MSIs can submit a Concept Outline at any time. Those that have been invited to submit a full proposal can submit a proposal based on that Concept Outline at any time during one of the submission windows.

NSF and its partners support the continued growth of a broad and diverse interdisciplinary research community for the advancement of AI and AI-powered innovation, providing a unique opportunity to broadly promote the NSF vision and core values, especially inclusion and collaboration. The Expanding AI Innovation through Capacity Building and Partnerships (ExpandAI) program aims to significantly broaden participation in AI research, education, and workforce development through capacity development projects and through partnerships within the National AI Research Institutes ecosystem.
 

Track 1: ExpandAI Capacity Building Pilots
Up to $400,000 total budget over two years

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.

Track 2: ExpandAI Partnerships
$300,000 to $700,000/year for up to 4 years

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.

Full sponsor guidelines

No Applicants. 

Projects and organizations funded must directly align with Livestrong's mission and purpose. Livestrong focus areas and funding priorities include:

• Nutrition
• Mental Health

Funding Priorities:

• Reaching the underserved
• Serving communities of color
• Defeating digital discord
• Equitable access to solutions

More information about the focus areas can be viewed here.
Please note that agency submission portal will open January, 2023. 

E. Corral
E. Madenci
A. Craig

P. Satam (Systems and Industrial Engineering)

This solicitation is a reissue of NSF 22-574 with a new external deadline. NSF has an institutional limit of one full proposal per institution.

The overarching goal of this solicitation is to democratize access to NSF’s advanced cyberinfrastructure (CI) ecosystem and ensure fair and equitable access to resources, services, and expertise by strengthening how Cyberinfrastructure Professionals (CIP) function in this ecosystem. It aims to achieve this by (1) deepening the integration of CIPs into the research enterprise, and (2) fostering innovative and scalable education, training, and development of instructional materials, to address emerging needs and unresolved bottlenecks in CIP workforce development. Specifically, this solicitation seeks to nurture, grow and recognize the national CIP [1] workforce that is essential for creating, utilizing and supporting advanced CI to enable and potentially transform fundamental science and engineering (S&E) research and education and contribute to the Nation's overall economic competitiveness and security. Together, the principal investigators (PIs), technology platforms, tools, and expert CIP workforce supported by this solicitation operate as an interdependent ecosystem wherein S&E research and education thrive. This solicitation will support NSF’s advanced CI ecosystem with a scalable, agile, diverse, and sustainable network of CIPs that can ensure broad adoption of advanced CI resources and expert services including platforms, tools, methods, software, data, and networks for research communities, to catalyze major research advances, and to enhance researchers' abilities to lead the development of new CI.

All projects are expected to clearly articulate how they address essential community needs, will provide resources that will be widely available to and usable by the research community, and will broaden participation from underrepresented groups. Prospective PIs are strongly encouraged to contact the Cognizant Program Officers in CISE/OAC and in the participating directorate/division relevant to the proposal to ascertain whether the focus and budget of their proposed activities are appropriate for this solicitation. Such consultations should be completed at least one month before the submission deadline. PIs should include the names of the Cognizant Program Officers consulted in a Single Copy Document as described in Section V.A. Proposal Preparation Instructions. The intent of the SCIPE program is to encourage collaboration between CI and S&E domain disciplines. (For this purpose, units of CISE other than OAC are considered domain disciplines.) To ensure relevance to community needs and to facilitate adoption, those proposals of interest to one or more domain divisions must include at least one PI/co-PI with expertise relevant to the targeted research discipline. All proposals shall include at least one PI/co-PI with expertise pertinent to OAC.

The project description should explicitly address the following additional items with emphasis suitable to the proposed work and goal(s) of the solicitation (note that this information will also be employed as additional solicitation-specific review criteria; see Section VI.A. for details):

1. Broadening Adoption of Advanced CI infrastructure and methods;
2. Integration with the Computational Science Support Network (CSSN);
3. Challenges recognizing and democratizing research CIP workforce development;
4. Building scalable and sustainable communities of CIP;
5. Recruitment and evaluation; and
6. "Collective Impact" Strategy: Coordination network and Backbone organization (or an alternative strategy).

No applicants // 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, in two categories:

• 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; and
• Category II, Innovative Prototypes/Testbeds: innovative forward-looking capabilities deploying novel technologies, architectures, usage modes, etc., and exploring new target applications, methods, and paradigms for S&E discoveries.

Resource Providers supported via this solicitation will be incorporated into NSF’s ACSS program portfolio. This program complements investments in leadership-class computing and funds a federation of nationally available HPC resources that are technically diverse and intended to enable discoveries at a computational scale beyond the research of individual or regional academic institutions. NSF anticipates that at least 90% of the provisioned resource will be available to the S&E community through an open peer-reviewed national allocation process and have resource users be supported by community and other support services. Such allocation and support services are expected to be coordinated through the NSF-funded “Advanced Cyberinfrastructure Coordination Ecosystem: Services & Support” (ACCESS) suite of services, or an NSF-approved alternative as may emerge. If this is not feasible for the proposed resource, proposers must clearly explain in detail why this is the case and how they intend to make the proposed resource available to the national S&E community.