Program overview This master's offers a rigorous, research-oriented mathematical education combining deep theory with applied skills. Core training covers analysis, optimisation and stochastics, while you also specialise in a chosen application area. The curriculum emphasizes numerical methods, visualization and dynamical systems to bridge abstract mathematics and real-world problems.
Practical and professional skills You will work on concrete problem solving using computers, gaining hands-on experience with simulation and optimisation software and developing specific computational calculation skills. The programme also focuses on building the capacity to independently explore and master new fields, enabling you to adapt your mathematical expertise to different scientific or engineering contexts.
What you should have / recommended background
This four-semester program combines classroom study with substantial practical training. Formal lectures and seminars are delivered throughout the first three semesters to build advanced mathematical theory and methods, while the fourth semester is reserved for completing the Master's thesis. The curriculum is designed so that taught content directly feeds into students’ research and project work.
A mandatory, semester-long case-study module places students in interdisciplinary teams to tackle an industry-inspired problem. Working with peers from other fields, you apply mathematical tools to realistic challenges—an experience that strengthens problem-solving, communication and project-management skills and can directly inform future employment, research projects or your Master's thesis. In addition, compulsory internships arranged in cooperation with partner companies provide on-the-job training and industry exposure; these collaboration programs also offer practical support for students preparing their theses.
Core components (requirements)
Key learning outcomes
Applicants must have completed a Bachelor's degree in mathematics or hold an equivalent qualification in a closely related field. Admission is based on academic preparation: you need to demonstrate that your prior studies are comparable to the Bachelor's degree in mathematics that the program expects and that your background meets the entry requirements of the Master's degree.
Equivalence and suitability are judged by the admissions office on the basis of your academic record. International applicants should be prepared to document their prior coursework and achievements so the committee can assess whether they match the program’s expected level and content.
Requirements (bullet points)
Winter Semester (International)
31 May 2026
Summer Semester (International)
30 November 2026
Winter Semester (EU/EEA)
31 May 2026
Summer Semester (EU/EEA)
30 November 2026
Graduates gain advanced mathematical and computational skills suitable for careers in industry and research. Typical employment sectors include manufacturing, software development, consulting, and research & development departments where abilities in simulation, optimisation, numerical methods and data analysis are in demand. The programme's mandatory internships and industry case studies also facilitate direct contacts with employers and practical experience relevant for thesis work and job placement.
For students aiming at academic careers, the programme provides the theoretical and methodological foundation for doctoral studies in mathematics, applied mathematics or related engineering and data-science fields. Those planning to work in the German-speaking region are advised to acquire German language skills (see programme recommendation) to increase opportunities in engineering and industry roles there.