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The school on Computational and Data Science for High Energy Physics (CoDaS-HEP) was created to fill a void in the training of graduate students and postdocs working in HEP. Training young researchers in the latest computational tools and techniques is essential to their future careers in both research and industry. To be successful today’s grad students require a mix of particle physics domain knowledge and advanced software skills. Relevant computing topics are however often missing from traditional physics coursework and, as young researchers begin their active research careers, they discover the need for these skills, but are no longer in a position to follow such courses.
Type
Organisation
Keywords
computational, data science, parallel programming, machine learning
Contact
codas-hep@googlegroups.com.
CoDaS-HEP
https://codas-hep.org/
https://training.cern.ch/content_providers/codas-hep
The school on Computational and Data Science for High Energy Physics (CoDaS-HEP) was created to fill a void in the training of graduate students and postdocs working in HEP. Training young researchers in the latest computational tools and techniques is essential to their future careers in both research and industry. To be successful today’s grad students require a mix of particle physics domain knowledge and advanced software skills. Relevant computing topics are however often missing from traditional physics coursework and, as young researchers begin their active research careers, they discover the need for these skills, but are no longer in a position to follow such courses.
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