An ICTP-IAEA Virtual Meeting
This School will assist Ph.D. students and other early-stage career researchers to develop their skills and understanding in the application of modern data science techniques to the calculation and evaluation of data relevant to the physics and behaviour of plasmas.
The properties of laboratory, industrial, astrophysical and fusion energy plasmas are determined by numerous atomic and molecular processes. Modelling such plasmas requires a large amount of data concerning its collisions, spectroscopic properties and plasma-material interactions, not all of which is directly accessible by experiment. Plasma physicists therefore turn to calculations and approximations to complete their data needs.
The last 10 years have seen a huge increase in the amount of computing power available to run the codes that calculate these data. Accompanying this expansion has been the development of so-called data science techniques which unify statistical methods, data analysis and machine learning.
This School will provide training for and knowledge-transfer between scientists working in the fields of computational plasma physics and data science. Participants are expected to have some experience with basic programming in a language such as Python.
More details are available at IAEA web site: https://amdis.iaea.org/workshops/ictp-2021b
M. BAUTISTA, Western Michigan University, USA
M.-L. DUBERNET, Paris Observatory - PSL, France
C. HILL, IAEA, Austria
L. MARIAN, IAEA, Austria
Y. RALCHENKO, National Institute of Standards and Technology (NIST), USA
E. STAMBULCHIK, Weizmann Institute of Science, Israel
U. VON TOUSSAINT, Max Planck Institute for Plasma Physics, Germany
Registration: There is no registration fee.
During the application process the applicants will be requested to upload poster abstracts in PDF format. Please make sure you use our templates to generate such PDFs. Templates are available below for download.