The Chair of Computational Mechanics of Building Materials in the Institute for Building Materials at ETH Zurich has an opening for a PhD student in the field of computational modeling for friction across scales.
Our research focuses on modeling micro- to meso-scale mechanical properties of engineering and biological materials and interfaces. At small scales, these materials and interfaces commonly present heterogeneities which directly affect macroscopic performance during deformation and failure mechanisms. Overall strength is influenced by random local defects that nucleate failure when critically loaded and propagate until global catastrophic failure occurs. Improving our fundamental knowledge of the link between small-scale structures and large-scale properties is needed to improve risk analysis of existing materials, structures and natural systems.
The objective of this project is to develop cutting-edge computational models of heterogeneous interfaces with complex frictional properties. These systems are relevant for many natural and man-made systems at various length scales, including tectonic faults, glaciers, tires, brakes, and MEMs. The developed models will link small-scale properties with large-scale systems, and simulate nucleation, propagation and arrest of local slip areas (e.g., earthquakes, stick-slip sliding). Simulation results will be analyzed to study the effect of stochastic properties and non-linearities, and will be compared with available experimental data and/or field data. Overall, this project will enable a better understanding of fundamental links across scales that govern the mechanics of friction in nature and engineering applications.
Prospective applicants should hold a MSc in an engineering, physics or a related discipline. A strong background in material science, solid mechanics, applied mathematics, computational science, or a related field is desirable. The candidate is expected to be fluent in English, to show and maintain scientific integrity, and to have programming experience. The successful candidate shows enthusiasm for conducting original research and strives for scientific excellence. The position is available with starting dates as soon as possible.