DOE: SCIENTIFIC MACHINE LEARNING FOR COMPLEX SYSTEMS DE-FOA-0002958
Sponsor: DOEInternal Deadline: 01/30/2023Institutional Submission Limit: 4Sponsor Deadline: 03/01/2023Program Website
DOE: SCIENTIFIC MACHINE LEARNING FOR COMPLEX SYSTEMS DE-FOA-0002958The DOE SC program in Advanced Scientific Computing Research (ASCR) hereby announces
its interest in 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.
The focus of this funding opportunity is on basic research and development at the intersection of
uncertainty quantification (UQ) and scientific machine learning (SciML) applied to the modeling
and simulation of complex systems and processes.
Pre-applications and applications that are out-of-scope will be declined without review.
This competition limits required pre-applications from USC (as lead organization) to four.
Your application submission MUST be coordinated with the Office of the Vice President for Research. Please send a two page abstract via email to Richard White (whitejrw@mailbox.sc.edu) by January 30, 2023.. In addition to the 2-page abstract, you should also submit a biosketch for the PI.
The pre-application deadline to DOE is March 1, 2023, with invited full applications due April 12, 2023.
Please see the FOA for more details at: https://science.osti.gov/ascr/-/media/grants/pdf/foas/2023/SC_FOA_0002958.pdf#:~:text=DEPARTMENT%20OF%20ENERGY%20%28DOE%29%20OFFICE%20OF%20SCIENCE%20%28SC%29,NUMBER%3A%20DE-FOA-0002958%20FOA%20TYPE%3A%20INITIAL%20CFDA%20NUMBER%3A%2081.049