This consecutive Master's programme is taught in English and builds on prior undergraduate study in mathematics. It is designed to equip you with the analytical and research skills needed to contribute to internationally oriented research teams or to work in industry. The course emphasizes both theoretical foundations and practical methods, preparing graduates for further research or professional roles that require advanced mathematical training.
The curriculum is flexible and allows you to tailor your studies by choosing from a broad set of specialisation options. Areas of focus include algebra; analysis and partial differential equations; functional analysis; geometry; dynamical systems; numerical analysis; and stochastics. Together these options cover a wide spectrum of core topics in pure and applied mathematics, so you can steer the programme toward abstract theory or applications.
You can incorporate interdisciplinary elements from fields such as biology, chemistry, computer science, physics and economics, making it easier to apply mathematical methods to real-world problems. The programme also supports gaining practical experience through internships at non-university research institutes or in industry, which can help bridge academic study and professional practice.
Requirements (check the university website for exact details)
This Master's curriculum totals 120 credit points (CP) and is organised into several module categories that let you build breadth and depth in mathematics while tailoring the degree to your interests. Core/basic modules establish essential foundations, advanced modules deepen theoretical and technical expertise, and specialisation modules allow focused study in specific mathematical areas. Professionalisation modules are included to help you prepare for career paths beyond the degree.
The programme balances rigorous mathematical training with practical career preparation and research experience. Basic and advanced modules ensure you gain a solid command of core concepts and advanced methods; specialisation modules develop competence in chosen subfields; professionalisation modules offer guidance on applying mathematical skills in industry, finance, research or education. The degree culminates in an independent research project: a Master's thesis (25 CP) supported by a Master's seminar (5 CP), completed in the fourth semester, which demonstrates your ability to perform and communicate original mathematical work.
Requirements (concise)
You must hold a first professionally qualifying university degree (for example, a Bachelor's degree or equivalent) in mathematics or a closely related discipline. Your prior studies need to include substantial mathematics content: at least 100 credit points (CP) in mathematics at a level comparable to a specialised mathematics degree, plus a further minimum of 20 CP from subjects where mathematical methods play a major role. These credit point totals are used to verify that you have the necessary mathematical background to succeed in the Master's programme.
If you are still completing your undergraduate degree, you may be conditionally admitted provided you can prove that your degree will be completed before the Master's programme begins and that your current study plan allows this. Be prepared to submit documentation (e.g., a current transcript, an expected graduation confirmation, or a statement from your home university) showing you will meet the requirement by the programme start date.
Winter Semester (International)
31 May 2026
Summer Semester (International)
31 December 2026
Winter Semester (EU/EEA)
1 September 2026
Summer Semester (EU/EEA)
1 March 2026
Graduates are well prepared for research careers, including doctoral studies and positions at universities or research institutes (including Max Planck and other international research groups). The programme's research orientation and the Master's thesis provide direct preparation for academically focused roles.
The strong mathematical training and option to integrate applied fields make graduates attractive to industry employers in data science, quantitative finance, software development, engineering, and modelling. Professionalisation modules and possible internships with companies or research institutions support the transition to industry roles and R&D positions.