R&D Intern: Modelling Damage in Recycled Al Alloys

Constellium SE; Voreppe; Sur place; EUR 6 700 - 10 000; Temps partiel

Résumé du poste

Constellium SE invites an intern to model damage nucleation and growth in recycled aluminium alloys. Based in the Paris region, the role collaborates with Mines Paris PSL and other research teams to develop and validate a micromechanical damage model using nano-tomography data.

The project covers literature review, data post-processing, RVE construction, model testing, and transfer to industrial R&D with training of engineers. Strong numeracy and communication are essential.

Qualifications

• Good knowledge in mechanics.
• Knowledge in physical metallurgy is a plus.
• Motivation for numerical work.
• Strong capacity to post-treat a significant amount of data from both simulations and experiments.
• Serious, autonomy, critical mind and creativity.
• Ability to interact with both academic and industrial partners.
• Interest for research and development type of work.
• Good level of English (written and spoken).

Responsabilités

• Literature review on failure mechanisms and modeling strategies.
• Post-treatment of nano-tomography scans to extract input data for the model.
• Build the initial representative volume element (RVE).
• Test the existing model and identify discrepancies with experiments.
• Implement model enhancements for inputs and outputs.
• Compare simulations with experimental results for fracture strain and damage initiation.
• Synthesize results, write reports and present to the team.
• Transfer to the industrial R&D center and train engineers to use it.

Connaissances

Mechanics

English

Formation

Engineering school or Master of Science

Description du poste

Constellium SE invites an intern to model damage nucleation and growth in recycled aluminium alloys. Based in the Paris region, the role collaborates with Mines Paris PSL and other research teams to develop and validate a micromechanical damage model using nano-tomography data.

The project covers literature review, data post-processing, RVE construction, model testing, and transfer to industrial R&D with training of engineers. Strong numeracy and communication are essential.