EPFL seeks a PhD candidate to develop interpretable AI models for coupled multiphysics in geomaterials, combining computational mechanics with machine learning.
This role sits at the crossroads of computational mechanics, geomaterial multiphysics, and interpretable machine learning. The successful candidate will work to uncover governing equations and constitutive relations for complex phenomena using both micromechanical simulations and experimental data, aiming to advance the understanding of geomaterial processes across various scales.
Responsibilities
- Help build a next-generation, data-driven framework for scientific discovery within the field of geomaterials.
- Create methods that bridge mechanics and artificial intelligence, such as physics-based multi-scale modeling, thermodynamics-informed machine learning, and neurosymbolic AI approaches.
- Manage and lead international partnerships with experimental research teams.
Requirements
- Hold a Master’s degree in Mechanics, Civil Engineering, Mechanical Engineering, Geophysics, Applied Mathematics, Computational Science, or a closely related discipline.
- Demonstrate strong programming abilities in Python, C, or C++, with solid experience in computational mechanics and scientific machine learning.
- Possess excellent written and oral communication skills in English.
What the company offers
- A fully funded doctoral position.
- A competitive salary and standard employment conditions.
- Access to exceptional research infrastructure and world-class computational resources.
- The opportunity to engage in innovative, interdisciplinary research at the Data-Driven Mechanics Lab.
- A world-class, multi-cultural work environment located on the shores of Lake Leman.
About the company
EPFL’s Data-Driven Mechanics Laboratory focuses on research that merges computational mechanics with artificial intelligence, fostering an environment for cutting-edge scientific inquiry.
- The laboratory encourages applications from researchers interested in the intersection of computational mechanics and AI.
How to apply
Documents to submit:
- Curriculum vitae
- Detailed transcripts
- Motivation letter
Quelle: öffentlich zugängliche Karriereseite des Arbeitgebers. Batchly ist nicht der Arbeitgeber und steht nicht notwendigerweise in einem Vertragsverhältnis mit dem Unternehmen.