About the degree programme
In addition to being a science in its own right, mathematics plays a fundamental role in the quantitative areas of practically all other academic disciplines, particularly in the natural sciences, engineering, business administration, economics, medicine, and psychology. Mathematical results permeate nearly all facets of life and are a necessary prerequisite for the vast majority of modern technologies – and as our IT systems become increasingly powerful, we are able to mathematically handle enormous amounts of data and solve ever more complex problems.
Special emphasis is placed on developing students' ability to formalize given problems in a way that facilitates algorithmic processing as well as enabling them to choose or develop, and subsequently apply, suitable algorithms to solve problems in an appropriate manner. The degree programme is theoretical in its orientation, with strongly application-oriented components. Studying this programme, you can gain advanced knowledge in the mathematical areas of Cryptography, Computer Algebra, Algorithmic Algebra and Geometry, Image and Signals Processing, Statistics and Stochastic Simulation, Dynamical Systems and Control Theory as well as expert knowledge in Computer Science fields such as Data Management, Machine Learning, and Data Mining.
Furthermore, you will have the chance to learn how to apply your knowledge to tackle problems in areas as diverse as Marketing, Predictive Analytics, Computational Finance, Digital Humanities, IT Security and Robotics.
The fully English-taught degree programme
A broad spectrum of subjects with a focus on algorithms
Excellent relations with businesses and industry
Numerous partnerships with universities abroad
Mathematicians continue to have outstanding career prospects, as they are highly sought after wherever high-level analytical thinking skills are a requirement. Their potential occupational fields are therefore less limited than is the case with medical doctors or engineers, who specialize in a specific sub-field of their discipline.
Outside of academic and research organizations, mathematicians find employment in nearly all private- and public-sector organizations. Nowadays, mathematicians' work typically makes heavy use of computing technology.
Traditionally, mathematicians are employed in the pharmaceutical industry, in the financial industry, insurance companies, consulting and business intelligence, market research, logistics, information technology and in the research and development departments of high-tech companies.
The core modules consist of two mathematics seminars and the presentation of your master's thesis.
The compulsory elective modules are divided into eight module groups:
Algebra, Geometry, and Cryptography: This module group imparts advanced results in the areas of algebra and geometry, which constitute the fundament for algorithmic calculations, particularly in cryptography but also in many other mathematical areas.
Mathematical Logic and Discrete Mathematics: The theoretical possibilities and limitations of algorithm-based solutions are treated in this module group.
Analysis, Numerics, and Approximation Theory: Methods from the fields of mathematical analysis applied harmonic analysis and approximation theory for modeling and approximating continuous and discrete data and systems, as well as efficient numerical implementation and evaluation of these methods, are the scope of this module group.
Dynamical Systems and Optimisation: Dynamical systems theory deals with the description of change over time. This module group is concerned with methods used for the modeling, analysis, optimization, and design of dynamical systems, as well as the numerical implementation of such techniques.
Stochastics, Statistics: This module group deals with methods for modeling and analyzing complex random phenomena as well as the construction, analysis, and optimization of stochastic algorithms and techniques used in statistical data analysis.
Data Analysis and Data Management and Programming: This module group examines the core methods used in computer science for the analysis of data of heterogeneous modalities (e.g. multimedia data, social networks and sensor data) and for the realization of data analysis systems.
Applications: In this module group, you will practice applying the mathematical methods learned in module groups 1 to 6 to real-world applications such as Marketing, Predictive Analytics, and Computational Finance.
Key Competencies and Language Training: In this module group, you will choose seminars that develop your non-subject-specific skills, such as public speaking and academic writing and other soft skills; you may also undertake internships. This serves to complement your technical expertise gained during your degree studies and helps to prepare you for your professional life after university.
Academic entry requirements
You are eligible for this degree programme if you have an undergraduate university degree in mathematics or a closely related degree with a mathematics component of at least 110 ECTS credits with a final grade of 2.7 under the German marking system or the relevant equivalent grade in a foreign marking system. Applicants who have not attained this minimum grade may still apply if they are among the best 70% of graduates of their cohort.
Unless English is the language of instruction for your prior university or secondary education, you should provide a language certificate at level B2 of the Common European Framework of Reference for Languages (CEFR).
Similarly, unless German is the language of instruction for your prior university or secondary education, you should provide proof of German language skills at level A1 CEFR (i.e. beginner's level). If you do not have German language skills at the time of application or enrolment, you will complete a compulsory, free German language course during the first two semesters of the programme.