General information
Organisation
The French Alternative Energies and Atomic Energy Commission (CEA) is a key player in research, development and innovation in four main areas :
• defence and security,
• nuclear energy (fission and fusion),
• technological research for industry,
• fundamental research in the physical sciences and life sciences.
Drawing on its widely acknowledged expertise, and thanks to its 16000 technicians, engineers, researchers and staff, the CEA actively participates in collaborative projects with a large number of academic and industrial partners.
The CEA is established in ten centers spread throughout France
Reference
SL-DES-26-0045
Thesis topic details
Category
Engineering science
Thesis topics
Development of machine learning algorithms to improve image acquisition and processing in radiological imaging
Contract
Thèse
Job description
The Nuclear Measurements Laboratory at the LNPA (Laboratory for the Study of Digital Technologies and Advanced Processes) in Marcoule consists of a team specializing in nuclear measurements in the field. Its activities are divided between developing measurement systems and providing technical expertise to CEA facilities and external partners (ORANO, EDF, IAEA).
The LNPA has been developing and using radiological imagers (gamma and alpha) for several years. Some of the developments have resulted in industrial products, while other imagers are still being developed and improved. Alpha imaging, in particular, is a process that allows alpha contamination zones to be detected remotely. Locating the alpha source is an important step in glove boxes, whether for a cleanup and dismantling project, for maintenance during operation, or for the radiation protection of workers. The alpha camera is the tool that makes alpha mapping accessible remotely and from outside glove boxes.
The objective of the thesis is to develop and implement mathematical prediction and denoising solutions to improve the acquisition and post-processing of radiological images, and in particular alpha camera images.
Two main areas of research will be explored in depth:
- The development of real-time or post-processing image denoising algorithms
- The development of predictive algorithms to generate high-statistics images based on samples of real images.
To do this, an experimental and simulation database will be established to feed the AI algorithms.
These two areas of research will be brought to fruition through the creation of a prototype imager incorporating machine learning capabilities and an image acquisition and processing interface, which will be used in an experimental implementation.
Through this thesis, students will gain solid knowledge of nuclear measurements, radiation/matter interaction, and scientific image processing, and will develop a clear understanding of radiological requirements in the context of remediation/decommissioning projects.
University / doctoral school
Information, Structures et Systèmes (I2S)
Thesis topic location
Site
Marcoule
Requester
Position start date
01/06/2026
Person to be contacted by the applicant
MAHE Charly
charly.mahe@cea.fr
CEA
DES/DPME//LNPA
CEA/DES/ISEC/DPME/SEIP/LNPA
BP 17171, 30207 Bagnols sur cèze Cedex
04.66.79.79.51
Tutor / Responsible thesis director
LAMADIE Fabrice
fabrice.lamadie@cea.fr
CEA
DES/ISEC/DMRC/STDC/LRVE
CEA - Centre de Marcoule
Bâtiment 57
BP 17171
30207 Bagnols-sur-Cèze Cedex
04 66 79 65 97
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