Machine Learning and Data Analysis for Nuclear Physics

Abstract:  The TALENT initiative, Training in Advanced Low Energy Nuclear Theory, aims at providing advanced and comprehensive training to graduate students and young researchers in all aspects of low-energy nuclear theory. TALENT offers intensive three-week courses on a rotating set of topics. General information on TALENT and past courses can be found at http://www.nucleartalent.org. This year, due to the COVID-19 pandemic we offer a fully online variant of the course on: Machine Learning and Data Analysis for Nuclear Physics It will be held via the ECT* in Trento, Italy, from June 22 to July 3, 2020. The principal instructors will be 1. Daniel Bazin (MSU/NSCL/FRIB), 2. Morten Hjorth-Jensen (MSU/NSCL/FRIB), 3. Michelle Kuchera (Davidson College), 4. Sean Liddick (MSU/NSCL/FRIB), and 5. Raghuram Ramanujan (Davidson College). Videos of the learning material, programs, and all digital learning material will be made available to participants before the lectures start in a dedicated Classroom on Microsoft Teams. During the week of June 22-26 and June 29 to July 3, we will have online live lecture sessions from 2 pm to 4 pm Central European Time (CET), with questions and answers sessions from 5 pm to 6 pm CET. The standard variant of this course, with in-person attendance, is postponed to the summer of 2021. For applications and more information for the online TALENT course, please go to the website of the European Center for Theoretical Studies in Nuclear Physics and Related Areas, ECT*. The link with more information and registration is at https://www.ectstar.eu/node/4472 All material with schedule etc. will be available at https://github.com/NuclearTalent/MachineLearningECT For more information: Contact: Morten Hjorth-Jensen (hjensen@msu.edu)