Results of the analysis of a survey for young scientists on training quality in HEP instrumentation software and machine learning
This addresses a training gap for early-career researchers in physics, but it is incremental as it builds on prior survey data to guide program improvements.
The study analyzed a survey of 174 early-career researchers in physics to assess training quality in instrumentation software and machine learning, finding that 70% of respondents lacked training for widely used open-source tools.
A 2021 study by the ECFA Early-Career Researchers Panel revealed that 71% of 334 respondents used open-source software tools in their instrumentation work, yet 70% reported receiving no training for these tools. In response, the Software and Machine Learning for Instrumentation group was formed in the ECFA Early-Career Researchers Panel to assess the accessibility and quality of training programs in machine learning and software for early-career researchers in experimental and applied physics. This group launched a new survey, reaching 174 participants. This report summarises the survey results in detail, and is intended to serve as a guiding document to improve the training programs that are available to early-career researchers.