Mathematics

This English‑taught MSc program covers a broad spectrum of modern mathematics, from abstract theory to computational techniques. Course offerings include applied analysis, algebra, numerical analysis, scientific computing, optimisation, mathematical physics, mathematical modelling, dynamical systems, geometry and visualization. The curriculum brings together analytical and computational perspectives so you can engage with both theoretical foundations and practical methods.

The program is highly flexible: you can concentrate on a specific area to prepare for research or an advanced technical role, or combine modules across different fields for a more interdisciplinary profile. That freedom makes it easy to tailor your studies to your interests—whether you aim to continue toward a PhD, work in industry (modelling, data science, simulation, optimisation), or apply mathematical methods in engineering, finance or technology.

Key facts / requirements

• Instruction language: English
• Coverage includes: applied analysis, algebra, numerical analysis, scientific computing, optimisation, mathematical physics, mathematical modelling, dynamical systems, geometry, and visualization
• Programme structure: very flexible — option to specialise in a focus area or to select a broad mix of courses
• For specific admission criteria, prerequisites, application deadlines and required documents, consult the university’s official programme page (requirements vary by applicant background)

Curriculum overview

The MSc is structured across four semesters. The first three semesters are devoted to taught components—advanced lectures and interactive seminars—that deepen theoretical understanding and introduce research methods. Seminars provide space for close engagement with current literature, problem solving, and oral and written presentation of mathematical ideas.

The fourth semester is reserved for the Master's thesis, an independent research project supervised by faculty. During this term you will apply techniques and knowledge gained in coursework to a focused problem, produce a substantial written thesis, and prepare the work for academic or professional use.

This sequence trains you to master advanced mathematical tools, to carry out independent research, and to communicate technical results clearly—preparing graduates for doctoral study, research positions, or quantitatively demanding careers.

Program requirements (curriculum-level)

• Three semesters of coursework delivered via lectures and seminars
• One semester dedicated to an independent Master's thesis (research and thesis submission)
• Active participation in seminars (reading, presentations, and written assignments)
• Integration of coursework knowledge into a supervised research project

Graduates acquire advanced theoretical and computational skills that prepare them for research positions, doctoral studies or professional roles in industry. Typical pathways include careers in academia and research institutions, data science and analytics, software and scientific computing, finance and quantitative modelling, engineering and technology firms, and consulting.

The programme's practical elements — such as the compulsory internship and industry contacts in the Munich area — help students build applied experience and employer connections, supporting transitions into specialist technical roles or further academic qualifications (PhD).