Publié: 14 juin 2024
Lausanne
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ENAC - PhD Position in Physics-Informed Machine Learning For Mechanics of Material Failure (ML)
The Data-Driven Mechanics Laboratory is seeking a highly motivated doctoral student to study physics- and thermodynamics- informed machine learning (ML) for the mechanics of material failure. The project focuses on learning the effective behavior of materials of civil engineering interest (granular geomaterials, structural materials) arising from complex microstructural mechanisms involving inelasticity and friction, as well as potential multiphysics couplings. It promises to push the boundaries of constitutive and multiscale modeling for these materials.
Research in this project involves a synergistic combination of numerical modeling, and physics- informed ML with the following key aspects:
Please email a single PDF consisting of:
to [emailprotected] , indicating in the subject "PhD Application PI-ML - Your Name" until July 15th 2024. Applications will be evaluated in the order that they are received. For inquiries please contact Prof. Kostas Karapiperis at the same email.
Expected Start Date: Fall/Winter 2024
Duration: 4 years (1-year fixed-term contract renewable annually according to EPFL rules)