Study Abroad
Guide to Professional & Degree Courses
Home Degree Course Search Education Systems Contact

M.Sc. Scientific Computing (Elite Network of Bavaria)

Degree awarded
Master of Science (M.Sc.)

Chair of Scientific Computing, Department of Mathematics, University of Bayreuth, D-95440 Bayreuth, Germany

+49 921 55 7151

E-mail address

Type of course
Full-time or part-time degree programme

Language of tuition

Length of course
4 semesters (2 years) for full-time study;
8 semesters (4 years) for part-time study

Date of commencement
Mid-October (Winter Term);
Mid-April (Summer Term)

Application deadline
The application process has to be completed by May, 15th for the following Winter Term or by November, 15th for the following Summer Term

Class size
About 10-20 students

Cost / fees
No tuition/course fees;
Administration fee of about 120 Euros per term.

Student grants / Financial assistance
International Students: Scholarships for international students can be awarded via the International Office of the University of Bayreuth.
German Students: Nomination for the Max-Weber Programme possible.

Student dorms are available.

Major recruiters of graduates of our programmes
Industry, IT-Companies, PhD programmes of major research institutions in Germany and abroad

Student profile
1. 55% national students, 45% international students
2. 80% male students, 20% female students
3. age range: 21 to 33

Admission requirements
The qualification of the international elite master’s programme Scientific Computing requires

1. A bachelor’s degree in Mathematics, Computer Science, Engineering, Natural Sciences (or a degree with equivalent content) and a final grade of 1.9 (according to the German grading system) or better.

2. Sufficient specialized knowledge in Numerical Mathematics with at least 16 credits.

3. Certification of proficiency in English at level B2 according to the Common European Framework of Reference of Languages.

Programme Director
Prof. Mario Bebendorf

Contact person for application
Maximilian Bauer
Chair of Scientific Computing, University of Bayreuth, D-95440 Bayreuth, Germany
Phone: +49 921 55 7152
Email: scientific-computing(at)

University of Bayreuth

M.Sc. Scientific Computing (Elite Network of Bavaria)

Scientific Computing – Why?

Numerical software is widely used to accelerate development cycles in industry and business: instead of time- and labour-consuming studies of product properties that utilize prototypes, products can be nowadays simulated and optimized using computers.

Demands for the capabilities of numerical simulation continue to grow with the need for models that are more and more precise, 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.

Work areas and knowledge transfer

The field addresses the entire workflow, including modelling; mathematical, numerical, and statistical analysis; optimisation; the implementation of algorithms on high-performance computers; and the visualisation of results. Many of these topics extensively rely on methodologies from Applied Mathematics and Computer Science.

Others traditionally belong to different disciplines in particularly application fields such as Physics, Chemistry, Biology, Geo- and Engineering Sciences. Only the emergence of Scientific Computing facilitated an effective transfer of knowledge between these areas.

Concept, Courses and Modules

The international master’s programme is geared towards 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, hard-working students to apply the state-of-the-art methods and tools of Scientific Computing to solution of challenging problems in modern technology and sciences.

This interdisciplinary approach starts with an in-depth understanding of the mathematical core of the problem, provides a wide overview of modern numerical methods for solving differential and integral equations and analysing large amounts of data, and finally supplies practical skills and experience around high-performance computing necessary to implement these solutions in the form of numerical software.

In summary, the foci of the programme include the following four main areas:
  • Module A: Numerical Mathematics (Numerical Methods for several types of Differential Equations, Approximation Methods, Optimisation)
  • Module B: Modelling and Simulation of many problems known from (Bio)Physics, (Bio)Informatics, Chemistry and Engineering Sciences
  • Module C: High-Performance Computing (Data Structures, Parallel Systems and Algorithms)
  • Module D: Scientific Computing (Complexity Reduction, Fast and Efficient Methods, Meshfree Methods, Data Analytics, Quantification of Uncertainty)
In addition, internships and so-called modelling seminars promote cooperation with industry and business early on. (usually in the first or second semester)

Partner Universities

Partners in Germany:
  • FA University of Erlangen-Nürnberg
  • University of Würzburg
  • DLR Göttingen
  • Fraunhofer ITWM Kaiserslautern
  • MPI Magdeburg
  • Konrad-Zuse-Institut Berlin
  • University of Hamburg / TU Hamburg-Harburg
Partners in Europe and world-wide:
  • IUT Belfort-Montbeliard
  • Vienna Univ. of Economics and Business
  • Univ. of Warwick
  • Univ. of Bozen
  • Czech Academy of Sciences
  • Univ. of Oxford
  • Universita degli Studi di Padova
  • Universita della Svizzera Italiana
  • University of Canterbury
  • University of Newcastle
  • Tel-Aviv University
  • Colorado State University at Fort Collins
  • German Institute of Science and Technology, Singapore
  • Institute of Computational Engineering and Sciences, Univ. Texas at Austin

About the University of Bayreuth

The University of Bayreuth is a young, research-oriented campus university. The University’s founding mission in 1975 was to support interdisciplinary research and teaching and to develop interdisciplinary research priorities with which it could strengthen its own profile.

Its research programmes and programmes of study are frequently updated and cover the natural sciences, law, business and economics, cultural studies, languages and literature.

A good instructor-to-student ratio, high performance standards, interdisciplinary collaboration, and academic excellence have allowed the University to maintain its strong position in the rankings.

The University of Bayreuth ranked 51st among the 414 best young universities in the world in this year’s Times Higher Education (THE) Young University Rankings out of 1,400 universities around the world. This university is also a top choice for studying law, business, and economics in Germany, as borne out in the university ranking published by the Centre for Higher Education (CHE).

The University of Bayreuth has been an international leader in African Studies for many years; the Bayreuth International Graduate School of African Studies (BIGSAS) is part of the Excellence Initiative by the German federal and state governments and the “Africa Multiple” Cluster of Excellence seeks to realign Bayreuth’s African Studies focus area on close cooperation with Africa partner institutions.

High pressure & High Temperature Research carried out at the Bavarian Research Institute of Experimental Geochemistry & Geophysics has established a strong reputation worldwide. Polymer research at the University is a frontrunner in the funding ranking published by the German Research Foundation (DFG), The University of Bayreuth has a tight international network of strategically selected university partnerships.

There are currently around 13,500 students enrolled in 151 different programmes of study offered by the University’s seven faculties. With around 1,500 members of the academic staff, 240 professors and roughly 1000 non-academic staff members, the University of Bayreuth is one of the region’s largest employers. Third-party funding for research reaches 52,449,000 Euros in 2019.