Institute of Mathematics
Teaching
Current and past courses, seminars and supervised theses.
Courses and seminars
Summer term 2026
- Introduction to Academic Work in Mathematics (Kruse)
- Linear Algebra II (Kruse)
- Advanced Seminar in Numerical Mathematics (Arnold, Kruse, Podhaisky)
Winter term 2025/26
- Foundations of Numerical Mathematics for teacher-training programmes (Hantke)
- Linear Algebra I (Kruse)
- Numerical Methods for Partial Differential Equations (Kruse)
- Advanced Seminar in Numerical Mathematics (Arnold, Kruse, Podhaisky)
Summer term 2025
- Analysis II for teacher-training programmes (Hantke)
- Mathematics B II (Hantke)
- Numerical Methods for Ordinary Differential Equations (Kruse)
- Probability Theory and Statistics (Kruse)
- Specialised Seminar: Numerical Mathematics (Kruse, Podhaisky)
- Advanced Seminar in Numerical Mathematics (Arnold, Kruse, Podhaisky)
Winter term 2024/25
- Analysis I for teacher-training programmes (Hantke)
- Numerical Mathematics for the Bachelor’s programme (Kruse)
- Theory and Numerics of Ordinary Differential Equations for teacher-training programmes (Hantke)
- Advanced Seminar in Numerical Mathematics and Probability Theory (Arnold, Kruse, Redmann, Podhaisky)
Summer term 2024
- Introduction to Academic Work in Mathematics (Kruse)
- Numerical Methods for Ordinary Differential Equations (Hantke)
- Probability Theory and Statistics (Kruse)
- Specialised Seminar: Numerical Linear Algebra (Kruse, Podhaisky)
- Advanced Seminar in Numerical Mathematics and Probability Theory (Arnold, Kruse, Redmann)
Winter term 2023/24
- Foundations of Numerical Mathematics for teacher-training programmes (Kruse)
- Monte Carlo Methods (Kruse)
- Advanced Seminar in Numerical Mathematics and Probability Theory (Arnold, Kruse, Redmann)
Summer term 2023
- Linear Algebra II (Kruse)
- Advanced Seminar in Numerical Mathematics and Probability Theory (Arnold, Kruse, Redmann)
Winter term 2022/23
- Linear Algebra I (Kruse)
- Numerical Mathematics (Kruse)
- Advanced Seminar in Numerical Mathematics and Probability Theory (Arnold, Kruse, Redmann)
Summer term 2022
- Numerics I, including Introduction to Academic Work in Mathematics (Kruse)
- Numerical Methods for Partial Differential Equations (Kruse)
- Advanced Seminar in Numerical Mathematics and Probability Theory (Arnold, Kruse, Redmann)
Winter term 2021/22
- Foundations of Numerical Mathematics for teacher-training programmes (Kruse)
- Monte Carlo Methods and Random Number Generators (Kruse)
- Advanced Seminar in Numerical Mathematics (Arnold, Kruse)
Summer term 2021
- Numerical Mathematics for Business Mathematics (Kruse)
- Numerics of Stochastic Processes (Kruse)
- Advanced Seminar in Numerical Mathematics (Arnold, Kruse)
Winter term 2020/21
- Numerics II (Kruse)
- Numerics of Evolution Equations (Kruse)
- Advanced Seminar in Numerical Mathematics (Arnold, Kruse)
Summer term 2020
- Numerics I (Kruse)
- Numerical Methods for Partial Differential Equations (Kruse)
- Advanced Seminar in Numerical Mathematics (Arnold, Kruse)
Winter term 2019/20
- Foundations of Numerical Mathematics for teacher-training programmes (Kruse)
- Monte Carlo Methods and Random Number Generators (Kruse)
- Advanced Seminar in Numerical Mathematics (Arnold, Kruse)
The archive lists earlier courses taught at TU Berlin.
Supervision of theses
We welcome enquiries about Bachelor’s and Master’s theses and academic theses for teacher-training programmes. PD Dr Maren Hantke and Prof. Dr Raphael Kruse are available as supervisors.
In general, students should have successfully completed at least one advanced course offered by our group. This course can provide a starting point for the thesis topic. Finding an appropriate topic often takes time, so we recommend contacting a potential supervisor early. Depending on the topic and prior knowledge, additional time should be allowed for reading and revisiting relevant foundations before registering and writing the thesis.
Please contact us during office hours or by email.
Completed Master’s theses
- Lars Lange (MSc Mathematics, 2020): “Analysis and Application of Stochastic Gradient Methods for Machine Learning”
- Johanna Weinberger (MSc Mathematics, 2020): “Numerical Methods for Stochastic Partial Differential Equations with Monotone Drift and Applications”, jointly supervised with Reinhold Schneider, TU Berlin
Completed Bachelor’s theses
- Albert Arzumanian (BSc Business Mathematics, 2024): “Efficient Algorithms for Random Number Generation: The PCG Family”
- Pascal Hüser (BSc Business Mathematics, 2022): “Error Analysis of Randomised Runge–Kutta Methods for Ordinary Differential Equations”
- Johann Christian Gebhardt (BSc Mathematics, 2022): “Introduction to Quantum Computers”
- Alexander Zinser (BSc Mathematics, 2022): “Monte Carlo Methods for Linear Partial Differential Equations Based on the Feynman–Kac Formula” (PDF)
- Tom Weber (BSc Mathematics, 2021): “Simulation and Analysis of Turing Patterns in the Gray–Scott Model”
The thesis archive lists work supervised at TU Berlin.