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Postdoc in Machine-Learning-Based Reconstruction of Dental Cone-Beam CT CNRS in France
Degree Level
Postdoc
Field of study
Computer Science
Funding
Available
Deadline
Nov 17, 2026
Country
France
University
CNRS
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About this position
This postdoctoral project is part of the collaborative Cone-Beam AI initiative linking Acteon, CREATIS, and the Institut de Mathématiques de Bordeaux (IMB). The work is focused on improving the quality of dental cone-beam computed tomography (CBCT) for diagnosis while reducing the radiation dose delivered to patients.
The recruited postdoc will develop new, more effective tomographic reconstruction algorithms, with a strong emphasis on machine learning and methods for solving inverse problems. The research sits at the intersection of medical imaging, reconstruction theory, and data-driven algorithm design.
Research activities include reconstruction from truncated data so that images remain as quantitative as possible inside the scanner field of view and beyond it, motion correction by estimating patient or scanner motion without relying on a preliminary reconstruction, correction of scattered X-ray radiation through deep-learning-based projection correction, and reduction of metal artifacts that degrade image quality and can interfere with diagnosis.
The postdoc will join CREATIS, a multidisciplinary laboratory with broad expertise in medical imaging and a major role in health technologies, and will be integrated into the tomoradio team. The position is based mainly at the Centre Léon Bérard in Lyon, within a local group embedded in the cancer center environment.
Funding details
Available
How to apply
Apply via the official job posting on the Choisir le service public portal. Submit your application through the provided link before the deadline.
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Prepare your application
Review drafts and confirm requirements with the university.
Make your next move.
Prepare your application
Review drafts and confirm requirements with the university.