Host institution: Ludwig-Maximilian-University Munich, Germany (LMU)
|main supervisor:||Heiner Igel and Alice Gabriel (LMU, D)|
|co-supervisor:||Yann Capdeville (University of Nantes, F)|
This position is filled
This PhD position is one of the 15 Early Stage Researcher (ESR) positions within the SPIN project. SPIN is an Innovative Training Network (ITN) funded by the European Commission under the Horizon 2020 Marie Sklodowska-Curie Action (MSCA).
SPIN will focus on training 15 PhD candidates in emerging measurement technologies in seismology. We will research the design of monitoring systems for precursory changes in material properties, all while optimizing observation strategies. The unique interdisciplinary and inter-sectoral network will enable PhDs to gain international expertise at excellent research institutions, with a meaningful exposure of each PhD to other disciplines and sectors, thus going far beyond the education at a single PhD programme.
Objectives: The observations indicative of nonlinear wave propagation as well as experimental concepts involving all motion components recorded by new sensors types (displacement, strain, and rotation) are currently not fully supported by classic 3C modelling schemes. We build on our decades-long experience in developing forward and inverse solutions in computational seismology to adapt computer programs serving the scientific tasks of all work packages in SPIN. In particular we 1) include nonlinear models for wave propagation, 2) provide test data sets to explore sensitivities of various nonlinear rheologies, 3) provide wave simulation scenarios across the scales from laboratory (rock), to local (crust), to global scales (incl. mantle), and 4) use scenario calculations to optimize the experimental design. This project transfers simulation technology to all other work packages and partly builds on the EU project ExaHyPE, that has developed a new scalable solver for large-scale supercomputers, and it links to ongoing collaboration on waves in strongly heterogeneous media (homogenization, CNRS-Nantes). We seek candidates with experience in numerical modeling, interest in theoretical wave propagation, and experience and enthusiasm for programming. The successful candidate will be able to work with implementations of simulation software on parallel supercomputers (e.g., SuperMUC-NG).
- Improved physical model for material response to stress and dynamic strain, resulting wave propagation
- Benchmark synthetic data set for multi-component large-N experiment at LSBB
- Multi-scale open source solver for nonlinear seismic wave propagation problems