Mathematics (MSc)

The University of Siegen offers a Master’s programme in Mathematics with a duration of four semesters. It is targeted at students with the university degree Bachelor of Science (BSc) in Mathematics or an equivalent subject like statistics. It offers two minors: Natural sciences and technology (electrical engineering, computer science, mechanical engineering, or physics) Business mathematics (economy or business information systems) The share of the minor is approximately 30%. The Master's degree programme documents increased mathematical competences and communication skills that make it possible to work intently scientifically and as an instructor in an (interdisciplinary) team and to assess and develop new methods. The degree programme teaches skills for analysis of abstract structures, recognising, phrasing and solving problems in mathematics and the minor. Subsequent doctoral studies (PhD) are possible. A mathematician is characterised not only by specialist knowledge, but in particular, by skills such as the ability to think abstractly, logically and to comprehend and structure complex tasks. Possible tasks in business and industry are: Creation of risk forecasts (insurance companies)/analysis of the rate developments in the area of financial management (shares, etc.) Improvement of the encoding techniques, e.g. for online banking and phone, internet, music and images Optimisation of itineraries, e.g. for trains, buses and aeroplanes Development of mathematical models (automotive, aerospace, steel industry, medicine) Processing and evaluation of data, e.g. in banks and insurances The degree concludes with a Master's thesis. This thesis is written independently, with regular meetings with a supervisor. The topic is set in advance in coordination with the supervisor, and it can be in any area of mathematics. It is possible to have the Master's thesis co-supervised with an industry partner. In each semester, the Department of Mathematics offers a variety of lectures and seminars in algebra, analysis, stochastics and optimisation. There is no fixed order for attending these. However, some lectures naturally presume prior knowledge. Necessary prerequisites for each module are listed in each module description.