PhD student ENGAGE 03

Context & Job description

Thesis Subject: Artificial intelligence for operator-intensive coherent X-ray imaging procedures

This PhD project will explore the potential of artificial intelligence (AI) for the automation of operator-intensive coherent X-ray imaging procedures. It is focussed on radiation damage monitoring, automated optimization of reconstruction parameters, and adaptive X-ray fluorescence scanning.

Synchrotron beamlines are scientific instruments that feature advanced metrology, environmental control, and many degrees of freedom for the positioning of various components. Due to the complex nature of synchrotron experiments, much time is spent at beamlines on routines such as sample screening, data acquisition monitoring, beamline behaviour monitoring, and manual optimization of reconstruction parameters.

While AI is increasingly used in various fields, synchrotron beamlines are yet to benefit from its potential. This PhD project will be carried out at beamline ID16A, which combines coherent X-ray imaging techniques and X-ray fluorescence (XRF) microscopy for studies of 3D morphology and composition at nanoscale.

Objectives include:

  • Develop and explore strategies for automated parameter optimization of the algorithms used at ID16A for the reconstruction of holographic X-ray tomography data and near-field ptychographic X-ray tomography data.
  • Develop a monitoring tool for the automated evaluation of the quality of acquired data and sample stability under X-rays.
  • Develop and explore strategies for advanced X-ray fluorescence imaging, such as adaptive step size for samples with localized features of interest.
  • Formulate a generic methodology for AI-based experiment automation

For further information please contact:

Dr Sylvain Bohic,, +33 (0) 4 76 88 28 52
Dr Peter Cloetens,, +33 (0) 4 76 88 26 50
Dr Dmitry Karpov,, +33 (0) 4 76 88 45 08

Expected profile

  • An MSc or equivalent diploma in one of the following relevant fields is required: Applied Mathematics, Engineering, Computer Science, Physics.
  • Knowledge and experience with Signal Processing and Artificial Intelligence.
  • Proficiency in a programming language such as Python, Julia, C, C++, etc.
  • Experience with a Machine Learning library such as TensorFlow, PyTorch, Keras etc.
  • Good academic records in the relevant fields.
  • High-level communication and writing skills.
  • Proficiency in oral and written English.
  • Good interpersonal skills and ability to work as part of an interdisciplinary team.
  • Experience with synchrotron radiation facilities is an asset
  • Compliance with the Marie Sklodowska-Curie mobility rule: candidates must not have resided or carried out their main activity (work, studies, etc.) in France for more than twelve months in the three years immediately before the date of recruitment
  • Eligibility: Early-Stage Researchers (ESRs) shall, at the time of recruitment by the host organisation, be in the first four years (full-time equivalent research experience) of their research careers and have not been awarded a doctoral degree

Working conditions

The successful candidate will be enrolled at the Université Grenoble-Alpes. The candidate will be hired by the ESRF (Grenoble, France). The contract is of two years renewable (subject to satisfactory progress) for one year.

The ESRF is an equal opportunity employer and encourages diversity.

If you are interested in this position, please apply via the ENGAGE website (not on the ESRF website) by 15 March 2022


This PhD is co-funded by the Marie Skłodowska-Curie COFUND project ENGAGE (grant agreement101034267), and applicants must follow the associated rules notably regarding mobility (see ). In particular, applicants must not have resided or carried out their main activity (work, studies, etc.) in France for more than 12 months in the last 3 years.


Company description

The European Synchrotron, the ESRF, is an international research centre based in Grenoble, France.

Through its innovative engineering, pioneering scientific vision and a strong commitment from its 700 staff members, the ESRF is recognised as one of the top research facilities worldwide. Its particle accelerator produces intense X-ray beams that are used by thousands of scientists each year for experiments in diverse fields such as biology, medicine, environmental sciences, cultural heritage, materials science, and physics.

Supported by 21 countries, the ESRF is an equal opportunity employer and encourages diversity.

This website uses cookies to ensure that we give you the best experience on our website. If you continue we assume that you consent to receive all cookies on all websites.
For further information, please click here >>.