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Scientific Machine Learning for Complex Systems is sponsored by DOE Office of Science, Advanced Scientific Computing Research (ASCR). This program supports 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.
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gov Maintenance Calendar Advancing Uncertainty Quantification (UQ) in Modeling, Simulation, and Analysis of Complex Systems Document Type:Grants Notice Funding Opportunity Number:DE-FOA-0000315 Funding Opportunity Title:Advancing Uncertainty Quantification (UQ) in Modeling, Simulation, and Analysis of Complex Systems Opportunity Category:Discretionary Opportunity Category Explanation: Funding Instrument Type:Grant Category of Funding Activity:Science and Technology and other Research and Development Expected Number of Awards:6 Assistance Listings:81.
049 -- Office of Science Financial Assistance Program Cost Sharing or Matching Requirement:No Original Closing Date for Applications:Apr 26, 2010 Current Closing Date for Applications:Apr 26, 2010 Archive Date:Jun 16, 2010 Estimated Total Program Funding:$ 3,000,000 Eligible Applicants:Unrestricted (i.e., open to any type of entity above), subject to any clarification in text field entitled "Additional Information on Eligibility" Additional Information on Eligibility:All types of domestic entities are eligible to apply, except other Federal agencies, Federally Funded Research and Development Centers (FFRDCs), and nonprofit organizations described in section 501(c)(4) of the Internal Revenue Code of 1986 that engaged in lobbying activities after December 31,1995.
## Additional Information Agency Name:Chicago Service Center Description:The Office of Advanced Scientific Computing Research (ASCR) of the Office of Science (SC), U.S. Department of Energy (DOE), hereby announces its interest in receiving applications for research addressing the mathematical and computational challenges of uncertainty quantification in the modeling and simulation of complex natural and engineered systems.
Link to Additional Information:FedConnect Grantor Contact Information:If you have difficulty accessing the full announcement electronically, please contact: Marilyn M. Oyler, Grant Analyst, 301-903-3604 marilyn. oyler@science.
doe. gov Alexandra M. Landsberg, Technical Scientific Program Contact, 301-903-8507 sandy.
landsberg@science. doe. gov Karen I.
Pao, Technical Scientific Program Contact, 301-903-5384 karen. pao@science. doe.
gov marilyn. oyler@science. doe.
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Based on current listing details, eligibility includes: Eligible applicants typically include universities, national laboratories, and other research institutions. Applicants should confirm final requirements in the official notice before submission.
Current published award information indicates See official notice Always verify allowable costs, matching requirements, and funding caps directly in the sponsor documentation.
The current target date is rolling deadlines or periodic funding windows. Build your timeline backwards from this date to cover registrations, approvals, attachments, and final submission checks.
Federal grant success rates typically range from 10-30%, varying by agency and program. Build a strong proposal with clear objectives, measurable outcomes, and a well-justified budget to improve your chances.
Requirements vary by sponsor, but typically include a project narrative, budget justification, organizational capability statement, and key personnel CVs. Check the official notice for the complete list of required attachments.
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Fire Science Innovations through Research and Education (FIRE) program is sponsored by National Science Foundation (NSF). This program invites innovative multidisciplinary and multisector investigations focused on convergent research and education activities in wildland fire. It supports research that can inform risk management and response, adaptation, and resilience across infrastructures, communities, cultures, and natural environments. Relevant topics include developing novel materials and methods for retrofitting existing buildings and remediating buildings following wildfire and smoke events.
The UKRI Policy Fellowships 2025, funded by the Economic and Social Research Council, offer 18-month placements for academics to co-design research with UK government and What Works Network host organizations. Awards range from £180,000 to £280,000 and support three fellowship tracks: core policy fellows, Natural Hazards and Resilience policy fellows, and What Works Innovation fellows. Applicants must hold a PhD or equivalent research experience, be based at a UKRI-eligible UK organization, and possess relevant subject matter or methodological expertise. Government-hosted positions target early to mid-career academics, while What Works fellowships welcome all career stages. Fellows work directly with policymakers to bridge academic research and policy development on pressing national and global challenges. The application deadline is July 15, 2025.