SMARTHEP: training PhD students in real-time analysis at the LHC and in industry
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| Format: | Preprint |
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2026
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| author | Albrecht, Johannes Boggia, Laura Bozianu, Leon Carey, Andrew Cocha, Carlos Doglioni, Caterina Gooding, James Andrew Hansen, Joachim Inkaew, Patin Iversen, Kaare Jawahar, Pratik Kirschenmann, Henning Magdalinski, Daniel Ohlson, Alice Olocco, Micol Monteagudo, Henrique Piñeiro Schramm, Steven Sokoloff, Mike Sopasakis, Alexandros Taccari, Leonardo Åstrand, Sten |
| author_facet | Albrecht, Johannes Boggia, Laura Bozianu, Leon Carey, Andrew Cocha, Carlos Doglioni, Caterina Gooding, James Andrew Hansen, Joachim Inkaew, Patin Iversen, Kaare Jawahar, Pratik Kirschenmann, Henning Magdalinski, Daniel Ohlson, Alice Olocco, Micol Monteagudo, Henrique Piñeiro Schramm, Steven Sokoloff, Mike Sopasakis, Alexandros Taccari, Leonardo Åstrand, Sten |
| contents | In this invited Editorial for Software and Computing for Big Science, we describe the SMARTHEP Innovative Training Network funded via the Marie Skłodowska-Curie Actions between 2021 and 2025. SMARTHEP trained 12 PhD students to advance machine learning and real-time analysis in high-energy physics experiments and industrial applications. We present the perspective of students, supervisors, and external observers of the network, concerning the work done within the network, the added value compared to ``typical'' PhD positions, and the emerging themes and directions from our experiences in the past four years. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_07089 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | SMARTHEP: training PhD students in real-time analysis at the LHC and in industry Albrecht, Johannes Boggia, Laura Bozianu, Leon Carey, Andrew Cocha, Carlos Doglioni, Caterina Gooding, James Andrew Hansen, Joachim Inkaew, Patin Iversen, Kaare Jawahar, Pratik Kirschenmann, Henning Magdalinski, Daniel Ohlson, Alice Olocco, Micol Monteagudo, Henrique Piñeiro Schramm, Steven Sokoloff, Mike Sopasakis, Alexandros Taccari, Leonardo Åstrand, Sten Physics Education High Energy Physics - Experiment In this invited Editorial for Software and Computing for Big Science, we describe the SMARTHEP Innovative Training Network funded via the Marie Skłodowska-Curie Actions between 2021 and 2025. SMARTHEP trained 12 PhD students to advance machine learning and real-time analysis in high-energy physics experiments and industrial applications. We present the perspective of students, supervisors, and external observers of the network, concerning the work done within the network, the added value compared to ``typical'' PhD positions, and the emerging themes and directions from our experiences in the past four years. |
| title | SMARTHEP: training PhD students in real-time analysis at the LHC and in industry |
| topic | Physics Education High Energy Physics - Experiment |
| url | https://arxiv.org/abs/2601.07089 |