Overview The MSc Mathematics at the University of Bremen is designed for students who already hold a Bachelor’s degree in mathematics and want to deepen their analytical and methodological skills while improving their career prospects. Taught in English, the programme is based at a young, innovative university located in the culturally rich and affordable city of Bremen—an environment that supports study and research alongside everyday student life.
Teaching, research and learning experience The Department of Mathematics (together with computer science) is research-active and places strong emphasis on high-quality university teaching. The master’s curriculum follows a research-based learning approach, giving you flexibility to pursue your own scientific interests and to take advanced courses led by specialised research groups. The department’s involvement in Collaborative Research Centres and Research Training Groups also opens up early opportunities for postgraduate research and doctoral pathways.
What you will gain and study options Graduates leave with a broad set of contemporary mathematical problem-solving techniques applicable in academia and a wide range of industries—high-tech, finance and insurance, software development, management consulting, medicine and digital communication are all common employer sectors. The programme also prepares students for doctoral study in mathematics. Core specialisation areas include Algebra, Analysis, Numerical Analysis, and Statistics/Stochastics. You can follow a more theoretical route (no secondary subject) or choose an application-oriented track that pairs mathematics with a secondary subject.
Requirements and study options (concise)
This master's curriculum centers on both theoretical and applied mathematics. Teaching and research strengths include algebra and topology, ergodic theory and dynamical systems, hyperbolic geometry, mathematical stochastics and statistics (with a special emphasis on multiple testing), and a range of applied topics such as inverse problems, AI methods, optimisation and optimal control, and discrete optimisation. These areas feed into course offerings and research opportunities you can pursue during the program.
You select a formal specialisation from four areas—Algebra, Analysis, Numerical Analysis, or Statistics/Stochastics—while taking courses in the remaining areas to broaden your mathematical background (sample study plans label these as “Specialisation A/B/C” and “Diversification A/B/C”). You may also choose to combine your mathematics studies with an application subject (optional) drawn from disciplines such as biology, chemistry, computer science, economics, electrical engineering, geosciences, mechanical engineering, philosophy, or physics. This structure lets you tailor the curriculum to your academic interests and career goals.
The first three semesters are organised around an individual study plan assembled from several module types: lectures (typically with weekly exercise sessions), graduate seminars, reading courses, and general studies. The program’s “Advanced Communications” component is delivered as two graduate seminars. The fourth semester is dedicated to writing and presenting the Master’s thesis, giving you concentrated time for independent research and formal presentation of your results. Sample curricula illustrate these options and combinations.
Key modules
Learning outcomes
Curriculum requirements (concise)
The formal entry criteria are defined in the programme's Admission Regulations. The core conditions you need to meet focus on the content and scope of your prior degree and a short written statement of purpose.
If you completed your undergraduate studies outside the European Credit Transfer and Accumulation System (ECTS), check how your credits are converted or contact the admissions office to confirm equivalence. Your cover letter should be in English and clearly state why you are applying and which mathematical area you intend to specialise in.
For full details and any additional formalities (deadlines, document translations, transcript requirements), consult the Admission Regulations or contact the programme’s admissions office.
Winter Semester (International)
30 April 2026
Summer Semester (International)
15 October 2026
Winter Semester (EU/EEA)
30 April 2026
Summer Semester (EU/EEA)
15 October 2026
Graduates gain advanced mathematical problem-solving skills that prepare them for careers in academia and a wide range of industries. Typical sectors include high-technology companies, finance and insurance, software development, management consulting, medicine-related data analysis, and digital communications. The programme also equips students to pursue doctoral studies in mathematics.
Beyond sector-specific roles, the degree develops transferable analytical and methodological competencies — such as modelling, statistical inference, numerical simulation and optimisation — that are highly valued by employers in interdisciplinary and data-driven environments.