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Find similar grantsEarly Career Research Program is sponsored by U.S. Department of Energy (DOE). This program provides funding to early-career researchers working on transformative energy-related research aligned with the Department of Energy's mission.
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Early Career Program | Department of Energy The DOE Office of Science Early Career Research Program provides an annual funding opportunity for researchers in universities and DOE national laboratories.
Established in 2010, this program supports the individual research programs of outstanding scientists early in their careers and stimulates research careers in the disciplines supported by the DOE Office of Science: Advanced Scientific Computing Research (ASCR), Biological and Environmental Research (BER), Basic Energy Sciences (BES), Fusion Energy Sciences (FES), High Energy Physics (HEP), Isotope R&D and Production (IP), and Nuclear Physics (NP).
You can find more information on the Early Career Research Program page . Matthias Schindler: Then and Now / 2013 Early Career Award Winner With his Early Career award, Matthias Schindler developed theoretical tools to help us understand the processes inside of protons and neutrons.
Marian Jandel: Then and Now / 2013 Early Career Award Winner Marian Jandel at the University of Massachusetts Lowell is obtaining precise nuclear data measurements to advance our knowledge of neutron reactions. Yuan Ping: Then and Now / 2013 Early Career Award Winner Yuan Ping developed measurement methods that helped scientists properly control fusion energy losses at the National Ignition Facility.
Lijuan Ruan: Then and Now / 2013 Early Career Award Winner Lijuan Ruan studies the strong force interactions that occur in the quark-gluon plasma created at Brookhaven Lab’s Relativistic Heavy Ion Collider. Sigrid Elschot: Then and Now / 2013 Early Career Award Winner Sigrid Elschot studies the effects of fast-moving meteoroids and small space debris that vaporize, ionize themselves, and produce plasma upon impact. Amy J.
Clarke: Then and Now / 2012 Early Career Award Winner In her work studying metals manufacturing at the Colorado School of Mines, Amy J. Clarke learns how to avoid defects and improve solidification. Silviu Covrig Dusa: Then and Now / 2012 Early Career Award Winner Silviu Covrig Dusa developed technologies to make precision measurements at subatomic scales possible in the search to answer fundamental questions.
Joshua Zide: Then and Now / 2012 Early Career Award Winner A new approach to materials by Joshua Zide and his team turns semiconductors into nanocomposites with different properties and new applications. Xiaodong Xu: Then and Now / 2012 Early Career Award Winner Xiaodong Xu studies the properties of single atomic layer semiconductors, looking for new materials and new ways to control electrical conductivity.
Junjie Zhu : Then and Now / 2012 Early Career Award Winner Developing new technologies to measure rare particle interactions is the work of physicist Junjie Zhu at the University of Michigan and CERN.
Based on current listing details, eligibility includes: Early-career researchers. Applicants should confirm final requirements in the official notice before submission.
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Research on Circular Economy, Smart Manufacturing, and Energy-Efficient Microelectronics is sponsored by U.S. Department of Energy (DOE) Advanced Materials & Manufacturing Technologies Office (AMMTO). This funding opportunity supports innovative technology R&D across the manufacturing sector with a focus on circular economy, smart manufacturing, and energy-efficient microelectronics. While the stated deadline for full applications has passed, AMMTO frequently issues similar solicitations, and this highlights a relevant area of interest for the DOE.
Scientific Discovery through Advanced Computing (SciDAC) Institutes is sponsored by U.S. Department of Energy (DOE) Office of Science, Advanced Scientific Computing Research (ASCR). This program supports scientific discovery through advanced computing. While the specific call details for new applications are not explicitly stated as open with a deadline, the program is ongoing and represents a significant funding opportunity for scientific computing research.
The Department of Defense FY2026 Defense University Research Instrumentation Program (DURIP) provides funding for U.S. universities to acquire research equipment and instrumentation in areas important to national defense, including AI and machine learning hardware. The program is administered jointly by the Army Research Office (ARO), Office of Naval Research (ONR), and Air Force Office of Scientific Research (AFOSR), with approximately $34 million available and 95 awards anticipated. DURIP funds the acquisition of specialized computing hardware for AI/ML research (GPU clusters, TPUs, neuromorphic processors), robotics and autonomous systems testbeds, sensor arrays and data collection systems for machine learning training, high-performance computing infrastructure for defense-relevant AI research, and laboratory equipment for human-AI interaction studies. The program specifically supports equipment that enhances research-related education in DoD-priority disciplines. While general-purpose computing is not eligible, computing equipment directly supporting DoD-relevant AI research programs qualifies. No cost sharing is required.
Innovate UK's Sovereign AI Proof of Concept programme funds proof of concept demonstrators of AI technologies with state-of-the-art performance across five strategic themes: fundamental AI research, materials discovery, biosciences and health, defense and national security, and AI-aided chip/hardware design. Individual project grants range from £50,000 to £120,000 (approximately USD $63,500-$152,400) from a total allocation of at least £1.6 million. Projects must be 1-3 months in duration, starting by January 2026 and completing by March 2026. The programme supports feasibility studies and industrial research, with funding covering up to 70% of costs for micro/small businesses, 60% for medium, and 50% for large organizations. Literature review studies and projects unable to scale are excluded.