Contenido

M.Sc. Scientific Computing funded by the Elite Network of Bavaria

© Universität Bayreuth
Interested in solving challenging problems in modern technology and science? Apply now!

Scientific Computing – Why?

Numerical software is widely used to accelerate development cycles in industry and business: instead of time-consuming and labour-intensive investigations of product properties using prototypes, products can nowadays be simulated and optimized on computers. Demands for the capabilities of numerical simulation continue to grow with the need for models that are progressively more precise and the incorporation of new problem areas such as data analysis (e.g., big data) and stochastic models (i.e., those containing uncertain data). All these fields are encompassed in the relatively young and forward-looking research area of Scientific Computing.

Why are you the right person?

This international master’s programme is designed for students working at the intersection of mathematics, computer science, and application fields. The programme’s objective is to offer a specialized educational background that enables highly qualified students to apply state-of-the-art methods and tools of Scientific Computing to solve challenging problems in modern technology and sciences.

Career and job opportunities

Graduates of this program receive in-depth training in numerical mathematics, high-performance computing, modelling, and simulation so that they are qualified for jobs from industry and IT companies. A steppingstone for such careers is the early contact – already during the studies – with industry and business. As a result of the excellent education, graduates are especially qualified for PhD programs of major research institutions in Germany and abroad.

Details on how to apply can be found here. Application deadline for the winter semester 2025/2026: May 15, 2025. The application period for the summer semester 2026 is September 1 to November 15, 2025.

For more information about the programme, please visit www.scientific-computing.uni-bayreuth.de.

© Universität Bayreuth

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