Intitulé de l'offre : Doctoral student (M/W) : Enhancing 3-Dimensional radiation mapping and dose estimation with machine learning techniques and a novel directional spectrometer (H/F)
Référence : UMR6534-AURGON-025
Nombre de Postes : 1
Lieu de travail : CAEN
Date de publication : jeudi 25 mai 2023
Type de contrat : CDD Doctorant/Contrat doctoral
Durée du contrat : 36 mois
Date de début de la thèse : 2 octobre 2023
Quotité de travail : Temps complet
Rémunération : 2 135,00 € gross monthly
Section(s) CN : Interactions, particles, nuclei, from laboratory to cosmos
Description du sujet de thèse
The task of mapping accurately radiation fields is central to many activities at nuclear facilities or at healthcare settings where personal dose needs to be accurately monitored. It is also an important task that would enable the practical development of techniques of online dosimetry where workers are tracked in environment and their dose are calculated in real time.
In environments where the radiation fields are unknown mapping 3D fields helps with planning and protecting people from hazardous level of radiations.
We propose a research project to explore, test and built a 3D mapping strategy based on the nFacet 3D segmented detector system. You will use the nFacet 3D detector and optimisation methods based on machine Learning to solve this optimisation problem. You will play a central role in developing the simulation, virtual environments, and mapping algorithms to solve realistic problems around non-standard radiation fields measurement and develop techniques to estimate better the effective dose E.
This project is cross-disciplinary, at the crossroad between hardware and software, sensing and imaging, virtual environments, and robotics.
You should have a M2 level in subatomic physics or equivalent, should have knowledge in nuclear physics, particle physics and radiation-matter interactions. A good level in software with some knowledge of Python ML libraries, sensing and imaging would be a very good start. During the thesis the student will receive the necessary training in dosimetry and radiation measurements as well as broader skills in simulation and data analysis.
Contexte de travail
The successful candidate will be assigned to the nFacet team, within the Laboratoire de Physique Corpusculaire de Caen (LPCC - UMR6534).
The LPC CAEN, with about 90 staff, is a joint research unit (UMR6534) depending on three supervisory bodies: the CNRS, the University of Caen Normandy (UNICAEN) and the Ecole Nationale Supérieure d'Ingénieurs de Caen (ENSICAEN). It is located on Campus 2 of the University of Caen Normandy (Campus Côte de Nacre) and is part of the research park of ENSICAEN (www.lpc-caen.in2p3.fr/).
Contraintes et risques
Exposition to Radiations. Travel in France and abroad expected.
This contract is funded by the "RIN 2022 Chaire Excellence : 00120837-22E03518 _ ALPHA, Région Normandie".