⚡️ Coronavirus (COVID-19) update
We have temporarily modified programmes to virtual learning classrooms, so that all the scheduled teaching can take place online. Programmes will start in November 2020 and, if required, teaching online and then change to on-campus learning.
The University of Bayreuth will be offering a new elite programme of study starting in Summer Semester 2019: Scientific Computing is one of only two new programmes of study to receive Bavarian funding in the scope of the Elite Network of Bavaria. The field of scientific computing addresses the mathematical modelling and efficient numerical computation of complex problems from technology, economics, and the natural sciences. Today's product research and development would be unthinkable without numerical simulations using computers. Specific applications of scientific computing range from crash tests to electromagnetic compatibility, optimisation of fuel cells, calculating prices of financial derivatives, and the simulation of biological processes. This new international degree programme in mathematics will enable the University of Bayreuth to prepare highly talented students for future challenges in the field of numerical simulation.
Profile of the Master’s Programme
Over the past several years, numerical simulations of phenomena in technology and the natural sciences have been shown to be an essential tool for accelerating development cycles in industry and businesses. Whereas researchers once had to meticulously study the properties of a product on the basis of prototypes, they are now simulated and optimised on computers. Demands on 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 parameter-dependent problems and models with uncertain data. This was triggered by the relatively young and forward-looking research area of scientific computing.
The field addresses the entire solution chain, including modelling; mathematical, numerical, and statistical analysis; optimisation; the implementation of algorithms on high-performance computers; and the visualisation of results. However, little attention has been paid to training students in this development. Graduates of mathematics are generally still limited to a basic understanding of numerics and scientific computing. Due to the high demands of studying mathematics, there is usually not much time left over to transfer newly acquired knowledge to neighbouring fields that represent intellectual challenges in their own right.
The objective of the international master’s programme is thus to provide a specialised range of courses that lead highly qualified, hard-working students towards the development and mathematical analysis of highly efficient numerical methods. It is a crucial point that highly complex problems are brought to a less complex numerical approximation (on parallel computers) via an understanding of their mathematical core. The master’s programme involves – and is motivated by – a number of courses in other subject areas (biochemistry, physics, computer science, and engineering), in which the simulation of demanding problems plays a crucial role. The programme is geared towards students working at the intersection of mathematics, computer science, and physics. This interdisciplinary approach enables students to achieve and apply their specialised understanding of efficient methods for solving differential and integral equations and analyzing large sets of data and to extend this know-how to other subject areas.
Fields of Employment
Thanks to its structure and selection of courses, the master’s programme are well-suited to getting top students involved in current research on scientific computing at an early stage. In particular, the content is divided up so as to allow for a fast-track option for doctoral research. Financial support is available for research visits to international experts. Students complete internships and modelling seminars in close cooperation with high-tech companies alongside their studies. This enables a smooth transition to a challenging position in the field.
Admission requirements include a bachelor's degree in mathematics and a component of numerical mathematics (or a degree with equivalent content) and a final grade of 1,9 or better.
Certification of proficiency in English at level B2 according to the Common European Framework of Reference of Languages. Additionally, basic knowledge in German at level A1 is required.