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Area Engineering
Test and development of CFD surrogate models for Engineering applications
Reference persons GIOACCHINO CAFIERO
External reference persons Francesca Sogaro
Research Groups 10- Fluidodinamica
Thesis type NUMERICAL AND DESIGN ORIENTED
Description Test and development of CFD surrogate models for Engineering applications within the Databricks environment
New AI-based surrogate models are revolutionising the engineering industry and Stellantis is committed to leveraging these new technologies in its processes and is exploring its internal ML ecosystem comparability with these new technologies.
The student will join the ICT Data Science and Machine Learning team of Stellantis and will work together with the lead ML Engineer and AI engineer to
identify open source readily available Deep Learning surrogate models for engineering application (research required)
Test identified technologies on small simulation datasets (students run)
Test on Stellantis datasets 3D (company provided)
The students will have the opportunity to develop AI model in python within the stellantis cloud environment
Deadline 26/09/2025
PROPONI LA TUA CANDIDATURA