Slots: Closed. In addition, no more than two pre-applications for each PI at the applicant institution. All four slots have been assigned.
Deadlines
Internal Deadline: Closed.
LOI: March 1, 2023, 5pm ET
External Deadline: April 12, 2023, 11:59pm ET
Award Information
Award Type: Grant
Estimated Number of Awards: The exact number of awards will depend on the number of meritorious applications and the availability of appropriated funds.
Anticipated Award Amount: A single- or multi-institutional team, whether for as a prime applicant with subawards or as collaborative application, is limited to a request of no more than $1,200,000 per year.
Who May Serve as PI: Individuals with the skills, knowledge, and resources necessary to carry out the proposed research as a Principal Investigator (PI) are invited to work with their organizations to develop an application. Individuals from underrepresented groups as well as individuals with disabilities are always encouraged to apply.
Link to Award: https://science.osti.gov/-/media/grants/pdf/foas/2023/SC_FOA_0002958.pdf
Process for Limited Submissions
PIs must submit their application as a Limited Submission through the Research Initiatives and Infrastructure (RII) Application Portal: https://rii.usc.edu/oor-portal/.
Materials to submit include:
- (1) Single Page Proposal Summary (0.5” margins; single-spaced; font type: Arial, Helvetica, or Georgia typeface; font size: 11 pt). Page limit includes references and illustrations. Pages that exceed the 1-page limit will be excluded from review.
- (2) CV – (5 pages maximum)
Note: The portal requires information about the PIs and Co-PIs in addition to department and contact information, including the 10-digit USC ID#, Gender, and Ethnicity. Please have this material prepared before beginning this application.
Purpose
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.
SUPPLEMENTARY INFORMATION 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. DOE is committed to promoting the diversity of investigators and institutions it supports, as indicated by the ongoing use of program policy factors (see Section V) in making selections of awards. To strengthen this commitment, DOE encourages applications that are led by, or include partners from Established Program to Stimulate Competitive Research (EPSCoR)2 states, that are underrepresented in the ASCR portfolio3 and applications led by individuals from groups historically underrepresented in STEM.
Visit our Institutionally Limited Submission webpage for more updates and other announcements.