Closed · DE-FOA-0001920 · CFDA 81.087 · Discretionary

Request for Information (RFI)- Machine Learning for Geothermal Energy and the Geosciences

Federal grant opportunity posted by Golden Field Office, cataloged on Grants.gov.

$1-$2
Award range
Closed
Status
June 6, 2018
Close date
1
Expected awards

The verdict

Request for Information (RFI)- Machine Learning for Geothermal Energy and the Geosciences is a closed discretionary listing from Golden Field Office that offered $1 -- $2 across 1 expected award. Future funding cycles may be published under the same CFDA number. PlainGrants indexes 839 other opportunities from Golden Field Office.

$1-$2
award range
Closed
application status
1
expected award
81.087
CFDA program

Archived opportunity record

Request for Information is closed (last close June 6, 2018). Check the agency catalog for replacement NOFOs. Golden Field Office still indexes 839 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 June 6, 2018

Posted May 7 Closes Jun 6

Est. Total Funding

$1

Expected Awards

1

Instrument

Other

Description

Department of Energy’s (DOE) Office of Energy Efficiency and Renewable Energy (EERE), invites input from the public regarding opportunities associated with applying machine learning techniques toward challenges in the geosciences that are relevant to geothermal energy. With the overall goals of establishing the practice of machine learning (ML) in the geothermal industry and maximizing the value of the rich datasets utilized in the geosciences, GTO is seeking input in three areas: Identifying the most promising applications of machine learning in subsurface R&D, building open community datasets capable of supporting the most advanced ML techniques, and leveraging crowd-sourced R&D through alternative funding mechanisms. As ML is already well- established in some industries, GTO is also very interested in feedback from outside of the geothermal community. The information requested is intended to advance GTO goals in geothermal development, though there are likely crosscutting applications with other industries operating in the subsurface. Opportunities for partnerships with other industries are also of interest. The purpose of this Request for Information (RFI) is to gather feedback from stakeholders prior to DOE potentially issuing a Funding Opportunity Announcement (FOA). This RFI is not a FOA: therefore, DOE is not accepting applications at this time. All responses to this RFI must be provided as an attachment (in Microsoft Word format) to an e-mail message addressed to machinelearninggeo@ee.doe.gov. Responses must be received no later than 5:00 PM EDT on June 6, 2018. The full content of the announcement can be found on the EERE Exchange website at https://eere-exchange.energy.gov.

Catch-all / unrestricted eligibility mark · DE-FOA-0001920

Grants.gov marks Request for Information 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: Other. Funding-activity code maps to Energy (EN). This eligibility-code string dominates the Golden Field Office book (634 peers, 75% of 840).

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

Agency Contact

Michael J. Weathers machinelearninggeo@ee.doe.gov

What to do next

Request for Information is closed; use the parent program and agency catalog for the next funding cycle.

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