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

This PhD position focuses on advancing intelligent instrumentation for nuclear physics research at the Grand Accélérateur National d’Ions Lourds (GANIL) in France. The project integrates artificial intelligence with physical laws to improve particle identification, detector calibration, and trajectory reconstruction within the VAMOS++ magnetic spectrometer. The successful candidate will develop robust, scalable methods to detect instrumental drift and maintain reliable physical measurements under changing experimental conditions. Supervision is provided by Antoine Lemasson within a collaborative research environment supported by public and private funding.

• Design and implement physics-informed artificial intelligence algorithms for trajectory reconstruction and particle identification in the VAMOS++ spectrometer
• Develop self-supervised detector calibration frameworks to handle changing experimental conditions and maintain data reliability
• Analyze experimental nuclear physics data to evaluate isotopic yields and fission properties
• Monitor spectrometer performance and implement automated detection of instrumental drift
• Collaborate with experimental physicists and researchers at GANIL to integrate machine learning models into existing acquisition pipelines
• Document methodologies, prepare scientific reports, and present findings at academic conferences and in peer-reviewed journals