AI and digital twins in metallurgy

Description de l'offre

One of the European Union’s objectives in climate change consists
of reaching net-zero greenhouse gas emissions by 2050. Such perspective puts the metallic materials industry, as a large contributor to carbon emissions, under tremendous pressure for change and
requires the existence of robust computational materials strategies to enhance and design, with a very high confidence degree,
new metallic materials technologies with a limited environmental
impact.

From a more general perspective, the in-use properties
and durability of metallic materials are strongly related to their
microstructures, which are themselves inherited from the thermomechanical treatments.

Hence, understanding and predicting microstructure evolutions
are nowadays a key to the competitiveness of industrial companies,
with direct economic and societal benefits in all major economic
sectors (aerospace, nuclear, renewable energy, naval, defense, and
automotive industry).


Keywords
Digital twins - IA - Computational Metallurgy - Interface
networks - Front tracking - ToRealMotion algorithms -
Mesh based algorithms - Deep learning strategy.

see more here : https://www.cemef.minesparis.psl.eu/wp-content/uploads/2023/04/Cifre_PhD_DigitalTwins.pdf

Apply on line : https://applyfor.cemef.mines-paristech.fr/phd/

Profil recherché

Candidate profile and skills:

Degree: MSc or MTech in Applied Mathematics, with
excellent academic record. Skills: Numerical Modeling,
programming, proficiency in English, ability to work
within a multi-disciplinary team.

Contact:
marc.bernacki@minesparis.psl.eu

Annual gross salary: about 29.4k€ plus additional benefits from TRANSVALOR S.A.