Study Computational Modeling and Simulation (Master) ✔ TU Dresden

Planned changes

For this course of study, changes are planned for the 2020/21 winter semester.

Admission requirements

The prerequisite for admission is a first higher education degree that has been recognised in Germany and that qualifies the student for entry into a profession; or a degree from a state or state-approved university of cooperative education in information technology, mathematics, natural sciences, economics or engineering.

In addition, English language skills at B2 level of the European Framework of Reference for Languages as well as special expertise in computer modelling are required.

Proof of the applicant’s particular suitability is provided by means of an aptitude assessment procedure in accordance with the Regulations for the Assessment of Suitability for the Master’s Programme in Computational Modeling and Simulation (Regulations for the Aptitude Assessment Procedure / Eignungsfeststellungsordnung) as amended.

Aptitude assessment procedure

Information and documents to be submitted
Information on the aptitude assessment as well as the regulations for aptitude assessment can be found on the faculty’s website.

Notes on the application process

If, at the time of application, proof of the first degree qualifying the applicant for a profession is not yet available, the application will be considered under the precondition that 80% of the credit points attainable for the degree have already been achieved based on completed module examinations or the final thesis and the colloquium (if applicable). A certification from the awarding institute of higher education (examination office) serves as proof of the above-mentioned academic achievements. You can find the appropriate form on the Admissions Office website.

General information about the degree program

This curriculum teaches the computational and mathematical foundations of Computational Modeling and Simulation across applications. This includes both learning of models from data (Data Science, Machine Learning, Inference) as well as computer simulations of models. Specialization and knowledge transfer is acquired in the application-specific Tracks.

Study contents

The foundations in mathematics, computer science, and natural sciences with a strong emphasis on computer-based modeling and simulation form the prerequisites for application-specific specialization in one of the offered Tracks. The foundations include in particular: algorithmic and computatonal foundations, basic machine learning, data analysis, parallel programming, high-performance computing, numerical methods, probability and statistics, computer graphics and data visualization, stochastics, planning and analysis of computer experiments, and competence in literature studies in at least two application domains.

1. Track Computational Life Science:
Computer modeling of biochemical networks, applied bioinformatics, modeling and simulation of biological systems and processes in space and time, statistical methods and experiment design, validation and verification of simulation results, dynamics of and on biological networks, mathematical biology, computational biophysics, scientific visualization in biology and medicine, particle methods, simulation of reaction networks, computer models in cognitive neuroscience, simulation methods for tissue biomechanics.

2. Track Computational Mathematics:
Numerical analysis, numerically solving partial differential equations with finite element methods, scientific computing, computational methods in mathematical biology, mathematical modeling, numerics of partial differential equations, scientific programming, optimization methods, computational methods for multifield problems, computational statistics and Monte-Carlo methods.

3. Track Visual Computing:
Data visualization, algorithms for forward problems and inverse problems, user interface design, computer graphics, computer vision and image processing, information visualization, interactive media and multimedia, virtual reality, augmented reality, advanced machine learning and artificial intelligence.

4. Track Computational Modeling in Energy Economics (partly taught in German!):
Modeling and simulation of electricity markets, energy economy, simulation of national energy market systems, modeling environmental ressources and environment protection regulations, scientific computing, numerically solving partial differential equations.

5. Track Computational Engineering:
Computational fluid dynamics, simulation of multi-body dynamics, numerical methods for multifield problems, finite element methods for continuum mechanics, computer-aided design and optimization of technical systems.

6. Track Logical Modeling:
Symbolic and subsymbolic approaches to artificial intelligence, formal methods for system analysis and design, knowledge representation and reasoning, machine learning, logic programming, problem solving and optimisation, mathematical logic, knowledge graphs and semantic technologies, ontology languages, system verification, classical and probabilistic model checking, models of computation and computational complexity, proof theory and inference algorithms.

Study documents

The official announcements of TU Dresden include all published regulations . Please use the search bar to find the document you need: Official proclamation

The regulations are also available on each institution’s website.