PhD student ENGAGE 01

Context & Job description

Thesis Subject: AI strategies for protein crystallography

Structural biology has been in the spotlight during the ongoing pandemic for its capability to provide atomic level understanding of public health and societal problems. Data collected at the synchrotron are interpreted by building a macromolecular model, which is then deposited in the protein data bank (PDB). For each structure deposited, tens if not hundreds of datasets are collected every day at synchrotron beamlines. This screening operation is an intrinsic part of macromolecular crystallography, as the quality of each single crystal is extremely variable and unpredictable.

In the last year artificial intelligence techniques such as alphaFold or RosettaFold have allowed a leap forward in the building of the macromolecule model. The application of machine learning methods to the experimental analysis is still limited and surely not a routine.

The goal of the project will be to use supervised learning for the detection of defects at the earliest stage of the data collection process, to target more specifically the most promising crystals.

The student will develop the analysis code, produce a curated library of training datasets and perform experiments to validate the method. Those tools will then be deployed through automation at synchrotron beamlines and extended to the calculation of more adapted data collection plans for each specific sample.

The successful candidate will join the newly formed Algorithms for Data Analysis team, whose mission is to provide cutting edge methods for the analysis of experimental data at the ESRF.

The work will be carried in strong collaboration with the structural biology group and its 7 beamlines.

Further information may be obtained from Gianluca Santoni (tel.: +33 (0)4 76 88 22 33, email:



Expected profile

  • Degree allowing enrolment for a PhD (such as MSc, Master 2 de Recherche, Laurea or equivalent) in physics, bio-chemistry, computer science or closely related field
  • Proven computational and numerical skills; knowledge of a modern programming language; experience in high-performance computing is desirable.
  • Knowledge of biochemistry and/or crystallography will be considered as a plus
  • Proficiency in English (working language at the ESRF)
  • 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.

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