OSCER users at OU, Do you plan to submit a proposal to the following program? DOE Scientific Machine Learning for Complex Systems If so, OSCER can provide a description of the machine learning resources (a) that we already have and (b) that we plan to purchase soon. See below for details. Henry >---------- Forwarded message ---------- >Date: Wed, 25 Jan 2023 16:41:22 +0000 >From: Research Information Services <[log in to unmask]> >Subject: LIMITED SUBMISSION: DOE Scientific Machine Learning >for Complex Systems > >LIMITED SUBMISSION > >DOE Scientific Machine Learning for Complex Systems > >Link to FOA > >https://science.osti.gov/-/media/grants/pdf/foas/2023/SC_FOA_0002958.pdf > >Synopsis > >The 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. > >Internal Submission Information: The University of Oklahoma >will be limited to no more than four (4) applications as the >lead institution in a single- or multi-institutional team. >If you are interested in submitting an application for this >solicitation, you must submit an internal application by >February 1, 2023. > >On the internal application please select "DOE Scientific >Machine Learning for Complex Systems" from the dropdown menu >for the Agency and Competition name. > >The internal application must be submitted online via this >link: Internal Application, > >https://ousurvey.qualtrics.com/jfe/form/SV_2lDPjSmZboDryjY > >and should include: > >* a one- to two-page description of the objectives and >technical approach of the proposed research > >* a CV for the lead PI > >* a list of potential team members if applicable > >Internal deadline for internal application –February 1, 2023 > >Agency deadline for Pre-Applications –March 1, 2023 > >Agency deadline for Applications –April 12, 2023 > >Disclaimer: While the Office of Research Services (ORS) >makes every effort to ensure that correct information is >released regarding all Sponsor funding solicitations, >it is still incumbent upon the researcher and his/her >designee(s) to reconfirm the accuracy of any information >provided in the Sponsor links. Sometimes, Sponsors change >or revise funding announcements without notice to the >recipients. Therefore, please review the most current >guidelines and conditions of a proposal solicitation >thoroughly and carefully before submitting your proposal.