LBNL Logo ONHS Funding Opportunity Report

Annual Recurring University Training and Research

Solicitation ID: DE-FOA-0003215

Agency: DOE

Type: Grant
Deadline: 2026-10-16T00:00:00 ET
Eligibility: Maybe (Topic Dependent)
Funding: N/A
Doc Type: BAA
Clearance: No
Program Manager: rtesinfo@hq.doe.gov
Last Updated: 2026-08-14 21:35
Analyzed File: DE-FOA-0003215-Part_2.pdf

Eligibility Reasoning

NOFO Part 1, Eligibility, provides the eligibility criteria specific to your application. ... NOFO Part 1, Eligibility—Eligible Applicants, provides NOFO-specific eligibility information.

Note: This is an AI-generated summary...

Summary

This Department of Energy (DOE) Funding Opportunity Announcement (DE-FOA-0003215), "Annual Recurring University Training and Research," is a grant or cooperative agreement to fund research and development at U.S. colleges and universities. The primary goals are to educate and train future scientists and engineers, support novel early-stage research, and enhance R&D opportunities for underrepresented communities, thereby equipping students with translatable skills for the U.S. workforce. The provided document (Part 2) is a standard companion to the main funding announcement (Part 1) and outlines the fixed, non-program-specific requirements for the application, review, and award administration process. It details standard procedures and policies regarding cost-sharing, eligibility, application content (e.g., SF-424, budget justifications, foreign connection disclosures), submission via eXCHANGE, review criteria, intellectual property rights under Bayh-Dole, U.S. manufacturing commitments, and post-award requirements such as Go/No-Go reviews and data management plans.

Overall Technical Areas

Artificial IntelligenceGenerative AI ApplicationsFossil Energy ResearchEnvironmental Research and DevelopmentEnergy Data ManagementScientific Software DevelopmentResearch Data CurationData-Driven ModelingCybersecurity ResearchEnergy Security AnalysisResearch Technology SecurityScientific Data Visualization

Probable LBNL Areas

N/A

Focus Areas

N/A

Potential LBNL PIs (Overall)

Note on PI Matching: These suggestions are generated through an AI-driven semantic analysis of LBNL staff profiles.

NameScoreOrganization
Gregory Lemieux0.78EESA | CESD | Earth System Sciences · Scientific Software Development
Zhe Bai0.76CSA | AMCR | Computer Science · Data-Driven Modeling
Tiffany Connors0.76CSA | NERSC | Data Center Department · Cybersecurity Research
Jingjing Zhang0.76ETA | Building Tech. & Urban Sys. | Whole Building Sys Dept · Energy Security Analysis
Eric Masanet0.76ETA | Energy Analysis | Systems & Energy Tech Analysis · Fossil Energy Research
Rory Schmick0.75ETA | Building Tech. & Urban Sys. | Bldg & Industrial App Dpt · Energy Data Management
Devarshi Ghoshal0.75CSA | SciData | Data Science Applications · Research Data Curation
Cory Snavely0.75CSA | NERSC | HPC Technology Department · Research Technology Security
Oliver Ruebel0.74CSA | SciData | Data & Computational Science · Scientific Data Visualization
Zachary Needell0.74ETA | Energy Analysis | Systems & Energy Tech Analysis · Environmental Research and Development

Fundamental Research Exemption (FRE)

Not Mentioned