INTERNSHIP: Spatio-temporal analysis of chemical reaction by X-ray tomo-ptychography M/F

Safran, an international high-technology group, is a major player in aerospace, space, and defense, with a strong commitment to Research and Technology. Safran Tech groups its R&T activities around innovative platforms, notably in digital technology via the STN platform. Within this platform, the PRISM unit is dedicated to research on advanced monitoring and control.

In this context, we are studying the crosslinking process of epoxy resins used in organic matrix composites (OMCs), which are essential for next-generation engines. Using advanced synchrotron analyses, such as X-ray tomo-ptychography, we have been able to observe the fine structure of carbon fibers and the dissolution of hardeners. This work aims to optimize the use of OMCs and reduce the sector's carbon footprint.

The proposed internship focuses on using artificial intelligence to segment and track different hardeners in tomographies, in order to quantitatively analyze their dissolution dynamics. The results will help better understand these complex phenomena and could lead to a scientific publication.

The intern's mission will be to:

• Analyze experimental data through image processing and machine or deep learning
• Use tools such as Python, Matlab, and specialized software (e.g., Dragonfly)
• Place the analyses carried out within their physical context
• Collaborate with Safran Tech experts and researchers under the supervision of Mr. Ducousso (Sensor and Instrumentation Expert, associate professor at the PIMM laboratory) and Arturo Mendoza Quispe (Expert in image processing for materials)

Bibliography:

[1] M. Ducousso, et al., X-ray tomo-ptychography of single micrometric carbon and basalt fibres, Carbon Trends, vol. 19, p. 100490, 2025.

[2] M. Ducousso, et al., Nanoscale observation of hardener dissolution in epoxy using X-ray tomo-ptychography, Journal of Chemical Physics (Submitted).

Your workplace will be located at Safran Tech, Digital Sciences and Technologies Department, 78114, Magny-Les-Hameaux.

The sought-after profile appreciates physical data analysis, image processing, and artificial intelligence, knows how to work independently and as part of a team, and has good communication skills.

Desired education: Engineering school or master's degree in physics, computer science, or applied mathematics.