Postdoc in CBCT Tomography & ML for Dental Imaging

CNRS; France; On-site; EUR 42,000 - 54,000; Full time

Job summary

CNRS seeks a postdoctoral researcher to advance tomographic reconstruction for cone-beam CT in dental imaging. The role focuses on developing high-performance algorithms, integrating machine learning to improve diagnostic image quality while reducing radiation dose.

Colleagues across CREAITIS collaborations will contribute to CBCT reconstruction, motion correction, scatter correction, and metal artifact mitigation.

Qualifications

• PhD in applied mathematics, computer science, or medical physics.
• Strong experience in medical image processing and numerical methods.
• Proficiency in Python and C++ (ITK, RTK) and fluency in English.

Responsibilities

• Develop new, high-performance tomographic reconstruction algorithms for CBCT, with emphasis on machine learning approaches.
• Work on CBCT reconstruction from truncated data within and beyond the scanner field of view.
• Address motion correction by estimating motion without a prior reconstruction using data consistency methods.
• Study and mitigate scatter radiation and metal artifacts using deep learning-based approaches.

Skills

Python

C++

Education

PhD in applied mathematics / computer science / medical physics

Tools

ITK

RTK

Job description

CNRS seeks a postdoctoral researcher to advance tomographic reconstruction for cone-beam CT in dental imaging. The role focuses on developing high-performance algorithms, integrating machine learning to improve diagnostic image quality while reducing radiation dose.

Colleagues across CREAITIS collaborations will contribute to CBCT reconstruction, motion correction, scatter correction, and metal artifact mitigation.