PhD Position Computational and Constitutive Modeling of Snow Mechanics

EPFL is pleased to invite applicants to apply for a new opening PhD position in computer science. Applications will be evaluated on a continuous basis.

The new group of Dr. J. Gaume at the Swiss Federal Institute of Technology of Lausanne (EPFL, Switzerland) invites applications by highly motivated, committed, and talented students/researchers for a PhD position in the field of computational mechanics for snow and avalanche modeling.

This group was created in the framework of the SNSF Eccellenza project “Unified modeling of snow and avalanche mechanics using the Material Point Method”. The group focuses on the development of new mechanical models to simulate and improve our understanding of snow and avalanche mechanics using a multi-scale framework. Simulations of snow microstructure deformation and failure will allow to define homogenized elastoplastic constitutive models which will be used to study crack nucleation and propagation, avalanche release and flow dynamics at the slope scale. Our simulations are based on the Material Point Method (MPM), a hybrid Eulerian-Lagrangian method particularly well suited to simulate large deformations, fractures, collisions and solid-fluid transitions. It was successfully used to model snow in the Disney movie “Frozen” (Stomakhin et al. 2015, SIGGRAPH) and complex processes involved in avalanche mechanics (Gaume et al. 2018, Nature Communications).

You will perform mechanical simulations of snow microstructure based on finite strain elastoplasticity (for the ice matrix) and the Material Point Method. Data of snow microstructures obtained through X-ray computer tomography at the SLF will be used as input geometry. You will analyze the influence of snow type, density, anisotropy on i) the stiffness tensor; ii) the yield surface and iii) the post-peak behavior of the samples for loading rates involved in natural and artificial snow avalanches. This will lead to the development of a fully homogenized elastoplastic constitutive model accounting for the ductile-to-brittle transition in snow able to reproduce classical snow behaviors such as compaction hardening but also more complex processes such as the propagation and reflection of compaction bands (Barraclough et al. 2017, Nature Physics). Results will be validated by comparing MPM simulations to laboratory experiments. You will publish your results will in renowned scientific journals, present them at international conferences and promote their transfer into practice.

Candidates should hold a Master's degree in (computational) mechanics, (computational) physics or computer science (or equivalent). Background/experience in solid mechanics, numerical modeling and c++ is mandatory. Additional experience with continuum numerical methods for solving partial differential equations such as the Finite Element Method and/or the Material Point Method is an advantage. The candidate should have very good English skills and excellent communication capabilities as most tasks will be done in collaboration with the other students and researchers of the group as well as with several external collaborations through exchange visits (SLF, UCLA, UPenn).

Contact : For additional information please contact Johan Gaume by e-mail

Please send your application (cover letter, detailed resume, copies of certificates and grades, names of 2 references and a one page summary of your MSc thesis) by e-mail to :


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