Mathematics (MSc)

Overview

Mathematics is central to interdisciplinary advances in technology and innovation, and its expanding, varied scope directly supports complex problem-solving that shapes the future. The Department of Mathematics builds on its track record in teaching and research to maintain a strong connection between research activities and classroom learning. This Master's programme is designed around that link, giving students a research-rich environment while retaining practical, career-oriented elements.

The programme’s primary aim is to train graduates to carry out independent research and to contribute effectively across sectors — including industry, commerce, education and research institutions. Teaching emphasizes research-related coursework and workplace-relevant training, delivered in a supportive environment where students develop the skills needed to pursue their own mathematical investigations.

Students receive close academic guidance and individual counselling in keeping with a long departmental tradition. As Lichtenberg, a former professor here, put it: people “are taught how to think rather than being continuously taught what they ought to think.” International collaboration is also a core feature: the programme strengthens students’ ability to work within global networks by institutionalizing cooperation with research organisations in and around Göttingen, elsewhere in Germany, and abroad.

Key points & expectations

• Language of instruction: English.
• Strong emphasis on research-based teaching combined with occupationally oriented training.
• Personal academic guidance and individual counselling for research development.
• International outlook with institutionalised cooperation and partnerships locally, nationally and internationally.
• Graduates are prepared for independent research and for roles in industry, commerce, education and research institutions.
• Students choose one of three specialised tracks: general research-oriented, mathematical physics, or mathematical data science.

This intensive, well-structured Master's programme builds directly on the mathematical knowledge you gained at undergraduate level, expanding and deepening core concepts while introducing contemporary directions in your chosen area of specialisation. A deliberate emphasis is placed on re‑examining classical mathematical themes through modern approaches and recent developments, so you graduate with both rigorous theoretical grounding and awareness of current research.

Teaching combines a wide selection of lectures, seminars and lab courses across pure and applied mathematics, with statistics integrated into the curriculum and the option to take minor subjects such as business administration, computer science, economics, philosophy or physics. Core and elective modules span algebra, analysis, geometry, number theory, topology, numerical analysis, optimisation, image processing, statistics, stochastics and mathematical data science—allowing you to tailor the programme toward theoretical or application‑oriented interests.

Beyond subject knowledge, the programme deliberately cultivates methodological and professional competencies: you gain expert-level mathematical methods, practical lab experience and improved soft skills to strengthen personal responsibility and employability. In the fourth semester you carry out an independent scientific project under supervision, demonstrating your ability to plan and complete research work. Part‑time study arrangements are also possible for greater flexibility.

Requirements / programme components (concise)

• Builds on and expands mathematics knowledge from undergraduate studies
• Selection of lectures and seminars from algebra, analysis, geometry, number theory, topology, numerical analysis, optimisation, image processing, statistics, stochastics, mathematical data science
• Lab courses and seminars to acquire methodological and practical skills
• Option to take minor subjects (business administration, computer science, economics, philosophy, physics)
• Development of soft skills and professional competencies
• Fourth‑semester supervised, independent scientific project
• Part‑time study option available

Graduates are prepared for a wide range of pathways in academia and industry. The programme's strong research component and supervised thesis make it a solid foundation for doctoral studies and careers in research institutions.

Alternatively, the analytical and methodological training equips students for roles in industry and commerce where quantitative and problem-solving skills are in demand—examples include positions in data science, quantitative analysis, software and technology development, finance, and research & development departments. The option to combine mathematics with minor subjects further broadens career flexibility.