PostDoc in the development of algorithms in image processing, electron diffraction (EBSD/TKD) a[...]

CNRS; France; Sur place; EUR 35 000 - 45 000; Plein temps

Résumé du poste

A leading research organization in France is seeking a postdoctoral researcher to adapt Radon transform techniques for high-angular-resolution analysis in EBSD. The role involves enhancing existing software, applying generative AI techniques, and collaboration with industrial partners. Candidates should have a strong background in software development, particularly in C++, along with expertise in image processing and generative AI. This full-time position offers a dynamic research environment and the opportunity for scientific publication and presentation.

Qualifications

• Demonstrated expertise in developing complex software solutions.
• Proficient in image processing and analysis.
• Proven expertise in generative AI.

Responsabilités

• Conduct bibliographic review on generative AI techniques.
• Enhance performance of existing software.
• Develop Radon transform and adapt to experimental diagrams.
• Collaborate with industrial partners.

Connaissances

C++ development

Image processing

Generative artificial intelligence

Collaboration skills

Presentation skills

Formation

PhD or equivalent in relevant field

Outils

Qt

MPI

OpenMP

Description du poste

Organisation/Company CNRS Department Laboratoire Georges Friedel Research Field Engineering » Materials engineering Physics » Acoustics Researcher Profile Recognised Researcher (R2) Country France Application Deadline 22 Dec 2025 - 23:59 (UTC) Type of Contract Temporary Job Status Full-time Hours Per Week 35 Offer Starting Date 3 Feb 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No

Offer Description

The HR-EBSD consortium, sponsored by three leading French industrial groups (SAFRAN-Tech, EDF, and CETIM) in collaboration with the Georges Friedel Laboratory (LGF) at the École des Mines de Saint-Étienne, sets out to develop an open-source software for high-angular-resolution analysis of EBSD diffraction patterns (HR-EBSD) that is both reliable and applicable to their material challenges.

EBSD/TKD techniques (Electron Backscattered Diffraction / Transmission Kikuchi Diffraction) are standard analytical methods employed in Scanning Electron Microscopy. The diffraction patterns produced by this method are direct projections of the crystal lattice examined by the electron beam.
The HR-EBSD/TKD method is designed to analyze localized residual stresses by quantifying the elastic distortions within the crystal lattice, which manifest as distortions in the diffraction pattern. It is presently constrained by its inherent relative nature, as it depends on image correlation techniques between a so-called reference image and a current image.

The StrainCorrelator software, developed internally by LGF over approximately fifteen years, provides a comprehensive platform for the analysis of residual stresses in relative mode.
To address the existing bottleneck caused by lack of knowledge of the mechanical state at the reference point, an innovative technique utilizing a Radon transform is currently being developed. The proof of concept is conducted using simulated diagrams. These are considerably easier to interpret than experimental diagrams, as they do not account for physical effects that are currently difficult to model. It has been shown that the Radon transform exhibits all the essential properties required for the determination of all diffraction parameters: source point location, crystal orientation, and the deviatoric component of the elastic strain tensor.

The primary objective of the individual appointed to this postdoctoral position will be to adapt the Radon transform to the context of experimental diagrams.

To accomplish this, generative AI techniques will be examined, either within the context of the experimental diagram itself or during the Radon transform analysis phase.

• Conducting a bibliographic review of generative AI techniques with the aim of exploring their applicability to the specified problem.
• Assuming responsibility for and enhancing the performance of the existing software;
• Development of the Radon transform and its adaptation to experimental diagrams;
• Deployment and implementation of the software with industrial partners;
• Scientific analysis and interpretation of the results;
• Preparation of scientific publications and presentation at conferences.

The designated individual will be affiliated with the Georges Friedel Laboratory at the School of Mines (Saint-Etienne, France). The LGF laboratory comprises approximately one hundred permanent researchers, post-doctoral fellows, and doctoral students specializing in the disciplines of materials, mechanics, and processes.

The research activity on High Angular Resolution EBSD is conducted under the leadership of Claire Maurice, CRHC CNRS, and is incorporated within the "Physics and Mechanics of Materials" (PMM) team.

This postdoctoral position is part of a consortium supported by three leading French industrial companies. The chosen candidate will collaborate closely with members of this consortium, notably Frédéric Adamski (SAFRAN-TECH), Dominique Loisnard and Maxime Mollens (EDF), as well as Anthony Nakhoul and Daniel Maisonnette (CETIM).

• Demonstrated expertise in developing complex software solutions (the current version of StrainCorrelator is implemented in C++, utilizing Qt for the graphical interface, alongside MPI and OpenMP for parallel processing). The door remains accessible for GPU programming or any other high-performance scientific language.
• Proficiency in image processing and analysis, along with an understanding of projective geometry.
• Proven expertise in generative artificial intelligence.
• Proficiency in SEM, EBSD, and continuum mechanics is desirable but may be developed during the postdoctoral tenure.
• Capacity to collaborate effectively within a team and engage with industry or academic stakeholders.
• Capacity to listen attentively and analyze expressed needs
• Ability to present one's findings through scientific publications in peer-reviewed journals and at international conferences.