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Quantum Machine Learning
Extending the European Competence Framework for Quantum Technologies: new proficiency triangle and qualification profiles
arXiv
Authors: Franziska Greinert, Simon Goorney, Dagmar Hilfert-Rüppell, Malte S. Ubben, Rainer Müller
Year
2024
Paper ID
38288
Status
Preprint
Abstract Read
~2 min
Abstract Words
159
Citations
N/A
Abstract
With the increasing industrial relevance of quantum technologies (QTs), a new quantum workforce with special qualification will be needed. Building this workforce requires educational efforts, ranging from short term training to degree programs. In order to plan, map and compare such efforts, personal qualifications or job requirements, standardization is necessary. The European Competence Framework for Quantum Technologies (CFQT) provides a common language for QT education. The 2024 update to version 2.5 extends it by the new proficiency triangle and qualification profiles: The proficiency triangle proposes six proficiency levels for three proficiency areas, specifying knowledge and skills for each level. Nine qualification profiles show prototypical qualifications or job roles relevant to the quantum industry, with the required proficiency, examples, and suggestions. This is an important step towards the standardization of QT education. The CFQT update is based on the results of an analysis of 34 interviews on industry needs. The initial findings from the interviews were complemented by iterative refinement and expert consultation.
Why This Paper Matters
- This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
- It adds a 2024 reference point for readers tracking recent quantum research.
- With the increasing industrial relevance of quantum technologies (QTs), a new quantum workforce with special qualification will be needed.
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