Postdoctoral Researcher in Computational Fracture Mechanics and Multiphysics Modelling of Snow and Ice – ERC Advanced Grant FRAMEGLOW
Pubblicato il 12-08-2026 - Politecnico Di Torino in Italia
Department of Applied Science and Technology
Organisation/Company Politecnico di Torino Department Department of Applied Science and Technology Research Field Physics » Computational physics Engineering » Mechanical engineering Researcher Profile Recognised Researcher (R2) Positions Postdoc Positions Application Deadline 1 Oct 2026 - 12:00 (Europe/Rome) Country Italy Type of Contract Temporary Job Status Full-time Offer Starting Date 1 Nov 2026 Is the job funded through the EU Research Framework Programme? Horizon Europe - ERC Is the Job related to staff position within a Research Infrastructure? No
Offer Description
Politecnico di Torino invites applications for a postdoctoral research position within the ERC Advanced Grant project FRAMEGLOW concerning computational modelling of fracture, friction and instability and wave propagarion in snow and ice under changing environmental conditions.
The researcher will be based at the Department of Applied Science and Technology, in the Physics area, and will work on the development and application of numerical models for fracture, friction,
wave propagation and dynamic instabilities.
The main activities will include:
- development and implementation of discrete and continuum mechanical models;
- simulation of nonlinear, multiscale and rate-dependent phenomena;
- analysis of fracture initiation and propagation;
- integration of numerical simulations with theoretical and experimental results;
- possible use of data-driven or physics-based machine-learning approaches;
A strong background in solid mechanics, fracture mechanics, computational mechanics is required. Good scientific programming skills and proficiency in written and spoken English are essential.
Experience in nonlinear mechanics, discrete models, finite-element methods, friction, dynamic fracture, multiscale modelling, machine learning or high-performance computing will be considered an advantage.
Previous experiencespecifically related to snow or ice is helpful b