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European Synchrotron Radiation Facility

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PhD Student in Neural-Network-Driven Reconstruction for Scanning 3D X-ray Diffraction European Synchrotron Radiation Facility in France

Degree Level

PhD

Field of study

Computer Science

Funding

Full funding available

Deadline

Sep 4, 2026

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Country

France

University

European Synchrotron Radiation Facility

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Keywords

Computer Science
Mathematics
Python Programming
X-ray Diffraction
Material Characterization
Artificial Neural Network
Open-source Software
Synchrotron Science
Crystalline Materials
Physics
Machine learning

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About this position

PhD opportunity at the European Synchrotron Radiation Facility (ESRF) in Grenoble, France, focused on developing neural-network-driven reconstruction tools for Scanning 3D X-ray Diffraction (S3DXRD). The project sits at the intersection of synchrotron science, materials characterisation, scientific machine learning, and open-source software development.

You will work with beamline scientists on ID11, ID03, and the ESRF Algorithms & scientific Data Analysis group to generate synthetic diffraction training data from simulated microstructures, train neural networks for indexing and reconstruction, and validate automated methods against conventional workflows. The scientific goal is to make grain-resolved orientation and strain mapping in crystalline materials faster, more robust, and more accessible to industrial users.

Key responsibilities include building a phantom microstructure generation pipeline, validating synthetic diffraction against real datasets, training and benchmarking neural-network indexing models from box-beam to full scanning geometry, collaborating with crystal plasticity simulation groups, and releasing an open-source reconstruction toolkit for the diffraction microstructure imaging community.

The PhD is hosted by Université Grenoble Alpes (UGA) within the Physics doctoral school and is based at the ESRF in Grenoble. The post is suitable for candidates with a background in Physics, Materials Science, Engineering, or a related field, and should be attractive to applicants interested in X-ray diffraction, advanced materials characterisation, Python programming, and machine learning.

Funding is provided through a paid PhD contract of two years, renewable for one additional year, with competitive compensation, allowances, and relocation support to Grenoble. The application deadline is 4 September 2026 at 23:59 (Europe/Paris).

For further information, contact James Ball at james.ball@esrf.fr.

Funding details

Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.

How to apply

Please submit your application including a cover letter, CV, academic transcripts, and contact information for two references. Applications should be sent via the online portal before the deadline.

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