Open Positions
Are you interested in joining our team? That is excellent news! We welcome individuals at any stage of their career. Whether you are seeking a role as a student assistant, doctoral researcher, or postdoctoral researcher, please feel free to contact us.
You will be an excellent fit for our group if you are enthusiastic about
- Developing new methods in applied mathematics and data science
- Implementing theoretical models and methods in reusable and performant software tools
- Applying modern methods and tools to real problems, e.g., from Medicine or Climate Science
Thesis Projects
We have a variety of exciting thesis projects available for students interested in topics at the interfaces of applied mathematics, machine learning in conjunction with simulation-based methods, and computer sciences. A selection of specific thesis projects is regularly listed below. However, we also offer other topics and encourage students to suggest their own ideas for potential thesis projects in these fields.
| Topic | Contact |
|---|---|
| Multilevel Gaussian Process Regression | S. Salatovic |
| Multilevel Regression for Optimal Experimental Design | S. Salatovic |
| J. Borodavka | |
| Is Gaussian process regression robust under weakly perturbed data? | J. Borodavka |
If you want to pursue your thesis project with us, email Prof. Dr. Krumscheid or the contact person listed above. Please share with us your interests and background.
Completed thesis projects
| Type | Title | Year | Supervisor |
|---|---|---|---|
| M.Sc. | Optimal Experimental Design in Isotopically Nonstationary Metabolic Flux Analysis | 2025 | S. Krumscheid |
| M.Sc. | Gaussian Processes for Cloud Controlling Factor Analysis | 2024 | S. Krumscheid |
| M.Sc. | Monte Carlo and Multi Level Monte Carlo Methods for Stochastic Elliptic Multiscale PDEs | 2024 | S. Krumscheid |
| M.Sc. | Prior Fields for the Inverse Problem of Cardiac Electrophysiology | 2024 | S. Krumscheid and M. Kruse |
| B.Sc. | Konsensbasierte Optimierung zur Hyperparameteroptimierung bei neuronalen Netzen | 2024 | S. Krumscheid |
| B.Sc. | Inference for Differential Equations via Probabilistic Numerics | 2024 | S. Krumscheid |
| M.Sc. | Explainable Hybrid Methods for Quality Assurance in End-of-Line Battery Testing | 2024 | S. Krumscheid |
| M.Sc. | Derivative Informed Learning of High-Dimensional Parametric Maps Induced by PDEs with Reduced Hessian Informed Neural Operators | 2024 | S. Krumscheid and M. Kruse |
| B.Sc. | Stochastic optimal control problems of a diesel generator in a microgrid | 2023 | S. Krumscheid |
| B.Sc. | Transport Maps: Sampling via optimal measure transport | 2023 | S. Krumscheid |
| M.Sc. | Polynomial Regression with Reduced Computational Cost: A Multilevel Least Squares approach | 2023 | S. Krumscheid |