PhD student W/M

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.

Thesis Subject: Microstructure and texture analysis of x-ray diffraction data using Machine Learning 

You will join a collaboration between the ID03 and Algorithms & Scientific Data Analysis teams at the ESRF to study the microstructure and texture of engineering materials.

Upon plastic deformation, the crystal lattice accumulates defects such as dislocations. With increasing deformation these dislocations self-organize into 3D structures such as grain and subgrain boundaries. Eventually this process leads to work-hardening. Beamline ID03 uses Dark Field X-ray Microscopy (DFXM) to study this microstructure in-situ and in 3D.

You will join the Algorithms & Scientific Data Analysis (ADA) group and develop machine-learning techniques to identify and characterize large-scale dislocation structures such as low-angle grain boundaries. Your objectives will be to:

- Segment 3D orientation maps acquired with DFXM into cells and subgrains.

- Identify and classify the boundaries between these cells according to their orientation with respect to the neighbouring (sub)grains, orientation change across the boundary, cell size, etc.

- Set up and evaluate the performance of various machine learning models

The project will bring much-needed automation of the data analysis workflows for DFXM, enable non-expert users to make better use of their data, and make the techniques more accessible to an even larger scientific community, and especially industry. All work will be carried out in close collaboration with the ESRF Dark-Field X-ray Microscopy beamline ID03.

Further information may be obtained from Carsten Detlefs (tel.: +33 (0)4 76 88 2556, email: detlefs@esrf.fr or Vincent Favre-Nicolin (tel.: +33 (0)4 76 88 2027, email: favre@esrf.fr) 

- Degree allowing enrolment for a PhD (such as MSc, Master 2 de Recherche, Laurea or equivalent) in physics, chemistry, computational science, or a related field.

- Knowledge of computational chemistry/physics software.

- Knowledge of a modern programming language (e.g., Python) and machine learning techniques is an asset.

- 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

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)

Link: https://engage.cyi.ac.cy/?page_id=36

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 http://ec.europa.eu/research/participants/portal/doc/call/h2020/h2020-msca-itn-2015/1622613-itn_2015_-_guide_for_applicants_v1_en.pdf). 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.