Doctoral student in Physics-Encoded Neural Network material modeling

Understanding and modeling material behaviour is central to many engineering challenges. This fully funded Doctoral student project, , aims to discover material models that give unprecedented accuracy and computational efficiency, enabling engineers to fully exploit the potential of materials.

This Doctoral student position offers the opportunity to work in an interdisciplinary research setting at the Division of Computational Mechanics and Materials Engineering, , in a collaborative and welcoming academic environment.

About us 

The Department of Industrial and Materials Science shares knowledge and their vision of technical solutions for the future industry in a sustainable society. Through excellent research, innovation, and education, we contribute to the development of future industrial value chains. 

In the division of Computational Mechanics and Materials Engineering, we foster an inclusive, friendly, and helpful work environment to which we welc...