Computational Physics
Computational Physics is a specialisation of the MSc programme in Physics. It is founded on the paradigm that practically all computational problems have a root in physics.
most problems in physics are too complicated for a straightforward comparison between theory and experiment, and even given the theoretical background, the consequences may be impossible to comprehend. Computational Physics builds a bridge between theoretical and experimental science, and with the advances in computing power, the field has become integral in almost all sciences. Also, the data handling itself has become part of the topic (Big Data).
In this specialisation you will use your physical understanding to develop advanced statistical methods and algorithms, and to work with simulation and data analysis on high scientific level. You will learn a number of methods enabling you to find the physics behind the data.
The specialisation allows you to solve a wide range of problems numerically. You learn to choose the optimal solution method and evaluate the fidelity of the result.
Computation physics spans courses within e.g. machine learning and data management, parallel computing, distributed systems and courses with a computational focus within a physics topic such as astrophysics, biophysics or geophysics.
Study Track
You can design a study track by choosing elective or restricted elective courses that allow you to delve more deeply into a given area during your specialisation. We have composed a study track which is particularly suitable for the specialisation in Computational Physics (click the link below to see the study track):
However, you may also choose to customise your programme with a mix of courses and projects that satisfy your own interests.
Programme structure
The Computational Physics specialisation can be structured in three different ways, depending on the size of your thesis as well as when you start working on your thesis.
Course of study 1 – thesis 45 ECTS:
| Block 1 | Block 2 | Block 3 | Block 4 | |
|---|---|---|---|---|
| Year 1 | Scientific Computing | Inverse Problems | Restricted elective course | Restricted elective course |
| Restricted elective course | Restricted elective course | Elective course | Elective course | |
| Year 2 | Restricted elective course | Thesis | ||
| Restricted elective course | ||||
Course of study 2 – thesis 60 ECTS
| Block 1 | Block 2 | Block 3 | Block 4 | |
|---|---|---|---|---|
| Year 1 | Scientific Computing | Inverse Problems | Elective course | Elective course |
| Restricted elective course | Restricted elective course | Restricted elective course | Restricted elective course | |
| Year 2 | Thesis | |||
Restricted elective courses
Choose your restricted elective courses from the lists below. Click on each course for a detailed description.
- Complex Physics
- Advanced Quantum Mechanics
- Biophysics of Cells and Single Molecules
- Earth and Climate Physics
- Theoretical Astrophysics
- Applied Statistics: From Data to Results
- Turbulence
- Computational Astrophysics: Star and Planet formation
- Dynamical Models in Molecular Biology
- Continuum Mechanics
- Signal and Image Processing
- Advanced Methods in Applied Statistics
- Concurrent and Distributed Systems
- Numerical Optimization
- High Performance Parallel Computing
- Diffusive and Stochastic Processes
- Applied Programming
- Advanced Mathematical Physics
- Dynamical Models for Climate and Numerical Weather Prediction
- Advanced Seismology
- Ocean Dynamics and Carbon Cycle
- Computational Methods in Simulation
- Applied Machine Learning