In this invited Editorial for Software and Computing for Big Science, we describe the SMARTHEP Innovative Training Network funded via the Marie Sk{\l}odowska-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.
@article{arxiv.2601.07089,
title = {SMARTHEP: training PhD students in real-time analysis at the LHC and in industry},
author = {Johannes Albrecht and Laura Boggia and Leon Bozianu and Andrew Carey and Carlos Cocha and Caterina Doglioni and James Andrew Gooding and Joachim Hansen and Patin Inkaew and Kaare Iversen and Pratik Jawahar and Henning Kirschenmann and Daniel Magdalinski and Alice Ohlson and Micol Olocco and Henrique Piñeiro Monteagudo and Steven Schramm and Mike Sokoloff and Alexandros Sopasakis and Leonardo Taccari and Sten Åstrand},
journal= {arXiv preprint arXiv:2601.07089},
year = {2026}
}