DOE Advancements in Artificial Intelligence for Science

Please see the full solicitation for complete information about the funding opportunity. Below is a summary assembled by the Research & Innovation Office (RIO).

Program Summary

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. The development of new AI techniques applicable to multiple scientific domains can accelerate progress, increase transparency, and open new areas of exploration across the scientific enterprise.

Each pre-application and application, as described in Section IV.B.2 and Section IV.D.2 respectively, must identify one primary research area.

  • Research Area 1: Extreme-Scale Foundation Models for Computational Science
  • Research Area 2: AI Innovations for Scientific Knowledge Synthesis and Software Development
  • Research Area 3: AI Innovations for Computational Decision Support of Complex Systems
  • Research Area 4: Federated and Privacy-Preserving Machine Learning and Synthetic Data Creation
  • Research Area 5: The Co-Design of Energy-Efficient AI Algorithms and Hardware Architectures

Out of scope are pre-applications and applications that:

  • Fail to focus on one of the research areas described above and indicate that research area as described in Section IV.B.2 and Section IV.D.2;
  • Fail to focus on fundamental advances in AI for science;
  • Fail to describe the kinds of scientific-computing workloads targeted by the proposed investigations;
  • Provide discipline-specific and/or application-specific solutions that do not generalize to multiple applications; or
  • Focus on the development of applications or approaches for quantum computers.

See the DOE solicitation for complete details.

Deadlines

CU Internal Deadline: 11:59pm MST March 4, 2024

DOE Pre-Application Deadline: 3:00pm MST March 19, 2024

DOE Application Deadline: 9:59pm MST May 21, 2024

Internal Application Requirements (all in PDF format)

  • Research Area (select one):
    • Research Area 1: Extreme-Scale Foundation Models for Computational Science
    • Research Area 2: AI Innovations for Scientific Knowledge Synthesis and Software Development
    • Research Area 3: AI Innovations for Computational Decision Support of Complex Systems
    • Research Area 4: Federated and Privacy-Preserving Machine Learning and Synthetic Data Creation
    • Research Area 5: The Co-Design of Energy-Efficient AI Algorithms and Hardware Architectures
  • Project Narrative (3 pages maximum): Please include: 1) Background/Introduction: explain the importance and relevance of the proposed work as well as a review of the relevant literature; 2) Project Objectives: provide a clear, concise statement of the specific objectives/aims of the proposed project; 3) Proposed Research and Methods: identify the hypotheses to be tested and details of the methods to be used including the integration of experiments with theoretical and computational research efforts; and 4) Promoting Inclusive and Equitable Research (PIER) Plan: describe the activities and strategies to promote equity and inclusion as an intrinsic element to advancing scientific excellence in the research project within the context of the proposing institution and any associated research group(s).
  • Lead PI Curriculum Vitae
  • Budget Overview (1 page maximum): A basic budget outlining project costs is sufficient; detailed OCG budgets are not required.

To access the online application, visit: https://cuboulderovcr.secure-platform.com/a/solicitations/6966/home

Eligibility

The PI on a pre-application or application may also be listed as a senior or key personnel, including in any role on a proposed subaward, on an unlimited number of separate submissions.

Limited Submission Guidelines

Applicant institutions are limited to no more than 3 letters of intent, pre-applications, or applications as the lead institution per research area.

Award Information

Ceiling: $350K per year

Floor: $100K per year

Anticipated Number of Awards: 6-8

Period of Performance: 3 years

Review Criteria

SCIENTIFIC AND/OR TECHNICAL MERIT OF THE PROJECT

  • What is the scientific innovation of the proposed research?
  • What is the likelihood of achieving valuable results?
  • How might the results of the proposed work impact the direction, progress, and thinking in relevant scientific fields of research?
  • How does the proposed work compare with other efforts in its field, both in terms of scientific and/or technical merit and originality?
  • Does the application specify at least one scientific hypothesis motivating the proposed work? Is the investigation of the specified hypothesis or hypotheses scientifically valuable?
  • Is the Data Management Plan suitable for the proposed research? To what extent does it support the validation of research results? To what extent will research products, including data, be made available and reusable to advance the field of research?
  • Does the Data Management Plan address the specific requirements the topic description?

APPROPRIATENESS OF THE PROPOSED METHOD OR APPROACH

  • How logical and feasible are the research approaches?
  • Does the proposed research employ innovative concepts or methods?
  • Can the approach proposed concretely contribute to our understanding of the validity of the specified scientific hypothesis or hypotheses?
  • Are the conceptual framework, methods, and analyses well justified, adequately developed, and likely to lead to scientifically valid conclusions?
  • Does the applicant recognize significant potential problems and consider alternative strategies?
  • Is the proposed research aligned with the published priorities identified or incorporated by reference in Section I of this FOA?

COMPETENCY OF APPLICANT’S PERSONNEL AND ADEQUACY OF PROPOSED RESOURCES

  • How well qualified is the research team to carry out the proposed research?
  • Are the research environment and facilities adequate for performing the research?
  • Does the proposed work take advantage of unique facilities and capabilities?

REASONABLENESS AND APPROPRIATENESS OF THE PROPOSED BUDGET

  • Are the proposed budget and staffing levels adequate to carry out the proposed research?
  • Is the budget reasonable and appropriate for the scope?

QUALITY AND EFFICACY OF THE PROMOTING INCLUSIVE AND EQUITABLE RESEARCH PLAN

  • Is the proposed Promoting Inclusive and Equitable Research (PIER) Plan suitable for the size and complexity of the proposed project and an integral component of the proposed project?
  • To what extent is the PIER plan likely to lead to participation of individuals from diverse backgrounds, including individuals historically underrepresented in the research community?
  • What aspects of the PIER plan are likely to contribute to the goal of creating and maintaining an equitable, inclusive, encouraging, and professional training and research environment and supporting a sense of belonging among project personnel?
  • How does the proposed plan include intentional mentorship and are the associated mentoring resources reasonable and appropriate?