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Thesis
Home   /   Thesis   /   Towards Intelligent VAMOS++: Physics-Informed AI for Adaptive and Reproducible Nuclear Instrumentation

Towards Intelligent VAMOS++: Physics-Informed AI for Adaptive and Reproducible Nuclear Instrumentation

Corpuscular physics and outer space Nuclear physics

Abstract

Recent developments at GANIL have demonstrated the opportunities opened by AI methods for trajectory reconstruction, particle identification and self-supervised detector calibration in the VAMOS++ magnetic spectrometer and associated detectors for fission studies.
This PhD project will extend these advances into an integrated framework for intelligent instrumentation, combining calibration, reconstruction, and performance monitoring. The objective is to develop robust, scalable and transferable methods that adapt to changing experimental conditions while preserving the reliability of physical observables.

Laboratory

Institut de recherche sur les lois fondamentales de l’univers
Département Grand Accélérateur National d’Ions Lourds
Grand Accélérateur National d’Ions Lourds
Caen Normandie
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