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PhD Position in Interpretable AI for Geomaterials

EPFL · Lausanne

Nouveau
Junior 🇬🇧 English
Python C++ Scientific machine learning Computational mechanics

Description du poste

About the role

The Data-Driven Mechanics Laboratory at EPFL is looking for a fully funded PhD student to work at the intersection of computational mechanics, multiphysics of geomaterials and interpretable machine learning. The project aims to discover governing equations and constitutive relations for key multiphysics phenomena using rich micromechanical and experimental data, with applications to geophysics, energy and sustainability.

Key responsibilities

  • Contribute to a next-generation data-driven framework for scientific discovery in geomaterials.
  • Develop techniques spanning mechanics and AI, including physics-based modeling across scales (discrete, mesoscale, continuum).
  • Work on thermodynamics-informed machine learning and neurosymbolic AI.
  • Lead international collaborations with experimental research groups.

Required profile

  • Master's degree in Mechanics, Civil Engineering, Mechanical Engineering, Geophysics, Applied Mathematics, Computational Science or a related field.
  • Excellent oral and written English.

Required skills

  • Strong computational and programming skills in Python and/or C++.
  • Computational mechanics and scientific machine learning.

What we offer

  • A competitive salary and employment conditions.
  • An innovative interdisciplinary research environment at the Data-Driven Mechanics Lab.
  • World-class research infrastructure and access to high-performance computing resources.

The contract starts in fall/winter 2026, is a one-year renewable contract for four years, and is fully funded. Candidates apply by sending a single PDF containing a CV (max. 2 pages), detailed transcripts and a motivation letter (max. 1 page) by July 15, 2026; applications are reviewed on a rolling basis.

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EPFL

Lausanne