Theses
Topics for theses will be found individually. If interested contact: klingenberg@mathematik.uni-wuerzburg.de
It makes sense to attend an AG or Seminar to get familiar with a topic.
Ongoing theses:
Master students:
| Gerhard Dill | Machine learning applied to an industrial process |
| Andrea Lörke | non-intrusive data-driven reduced-order modeling for time-dependent parametrized problems coupled with uncertainty quatification |
| Annika Gutzeit | low Mach and well-balanced num. methods for Euler w. gravity using relaxation Riemann solvers |
| Melissa Lange | optimal transport for seismic inverse problems |
| Miriam Schönleben | computing 2-dim. linear elastcity with enhancements by deep learning |
| Simon Wenchel | a GPU implementation of a discontinuous Galerkin method applied to the Cahn-Hillard equation |
| Sophie Lauer | Convex integration applied to multidimensional compressible Euler equations |
| Thomas Schuster | using neural networks for efficient numerical simulations of compressible flow |
Bachelor students:
Find more thesis in the list of finished theses.
