Closed · DE-FOA-0002122 · CFDA 81.049 · Discretionary

Scientific Machine Learning and Artificial Intelligence: Uncertainty Quantification

Federal grant opportunity posted by Office of Science, cataloged on Grants.gov.

$150K-$150K
Award range
Closed
Status
May 31, 2019
Close date
6
Expected awards

The verdict

Scientific Machine Learning and Artificial Intelligence: Uncertainty Quantification is a closed discretionary listing from Office of Science that offered $150,000 -- $150,000 across 6 expected awards. Future funding cycles may be published under the same CFDA number. PlainGrants indexes 414 other opportunities from Office of Science.

$150K-$150K
award range
Closed
application status
6
expected awards
81.049
CFDA program

Archived opportunity record

Scientific Machine Learning and Artificial In… is closed (last close May 31, 2019). The parent program page for CFDA 81.049 is the reliable place to catch re-announcements. Office of Science still indexes 414 other opportunities here.

According to Grants.gov (extract vintage 2026-08-10), this record reflects the officially published listing. See methodology.

Deadline tracker

Application window closed

Closed May 31, 2019

Posted Apr 16 Closes May 31

Est. Total Funding

$2,000,000

Expected Awards

6

Instrument

Grant

Description

In support of the Executive Order on Maintaining American Leadership in Artificial Intelligence, the DOE Artificial Intelligence (AI) Program and DOE SC program in Advanced Scientific Computing Research (ASCR) hereby announce their interest in the co-design of learning systems and AI environments that significantly advance the field of AI for public benefit within DOE’s Congressionally-authorized mission-space. The principal focus of this FOA is on Uncertainty Quantification (UQ) for AI validation and prediction. Foundational research is needed for strengthening the mathematical and statistical basis of validating machine learning and AI predictions from data generated by the Office of Science’s user facilities and scientific simulations. A critical open question for scientific machine learning (SciML) is: How do we make reliable predictions and uncertainty estimates from machine learning and AI models? Predictions can be greatly improved by including input uncertainties and insights from model discrepancies. Research advances will be needed in methods that incorporate mathematical, statistical, scientific, and engineering principles for uncertainty estimates in extrapolative predictions. Furthermore, extensive literature in statistics can be leveraged for improving the model validation process. Advances in UQ will greatly enhance the mathematical and scientific computing foundations for accelerated research insights from SciML and AI.

Catch-all / unrestricted eligibility mark · DE-FOA-0002122

Grants.gov marks Scientific Machine Learning and Artificial In… with a catch-all / unrestricted eligibility code (Unrestricted / see official listing). Read the official announcement text for the real applicant filter — the code alone is not a door list. The extract does not mark applicant cost-sharing as required. Instrument: Grant. Funding-activity code maps to Science and Technology / R&D (ST). This eligibility-code string dominates the Office of Science book (278 peers, 67% of 415).

Code 99
Unrestricted / see official listing

Codes are Grants.gov eligibility category values from the extract vintage 2026-08-10. Confirm the full eligibility statement on the official listing or the Grants.gov eligibility reference.

Official Listing on Grants.gov

View full details, application forms, and submission instructions.

View on Grants.gov

Parent Grant Program

CFDA 81.049

Basic Energy Sciences

U.S. Department of Energy

View program →

Agency Contact

Steve Lee Program Manager Phone 301-903-5710

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What to do next

Scientific Machine Learning and Artificial In… is closed; use the parent program and agency catalog for the next funding cycle.

  • Parent CFDA 81.049 may publish future NOFOs under the same assistance listing. Open program
  • Basic Energy Sciences indexes 6 Grants.gov listings in this extract. Program profile
  • Office of Science lists 414 other indexed opportunities on PlainGrants. Agency catalog

Opportunity deadlines and eligibility change on Grants.gov; PlainGrants mirrors the extract and is not the submission system.

Disclaimer: This information is sourced from Grants.gov and SAM.gov and is for informational purposes only. Opportunity details, deadlines, and eligibility requirements change frequently. Always verify current information directly on Grants.gov before applying. PlainGrants is not affiliated with any federal agency.

Read our methodology - how this data is sourced, computed, and verified.

Data sourced from the SAM.gov Assistance Listings and Grants.gov. See our methodology for details. Retrieved and formatted by PlainGrants