The student can then choose one of the following specialisations.
Computational Science and Engineering (CSE)
CSE is a rapidly growing multidisciplinary field of study with links to engineering, mathematics and computer science. This specialisation focuses on mathematical modelling and simulation of problems arising in science and engineering, the mathematical analysis of such models, and the development of new techniques for solving these problems.
There are major industrial and economic interests at stake when it comes to mathematical modelling since the properties of not (yet) realised technical or physical systems can be predicted and optimised better using computational and mathematical models. Hence there is a demand for experts, especially at large companies and research institutes.
For courses offered by the specialisation Computational Science and Engineering, see the online studyguide.
Discrete Mathematics and Optimization
Discrete Mathematics and Optimization provides the mathematical tools required for the analysis and solution of problems that are of a combinatorial nature. Such problems often have origins in (pure) mathematics, adjacent areas like computer science and quantum physics, or practical applications such as logistics.
The specialisation has a strong theoretical component, but also offers the opportunity to look into real-life applications in the field of (healthcare) logistics, machine learning, energy etc.
For courses offered by the specialisation Discrete Mathematics and Optimization, see the online studyguide.
Financial Engineering is a flourishing field of applied mathematics in the intersection of stochastic processes, statistics and numerical analysis, with the aim of solving challenging problems arising in economics and finance. This specialization covers a broad range of topics: from the basics of mathematical finance and financial markets to risk management, computational methods for finance, and all the way to statistical and deep learning methods for finance.
The demand for experts in Financial Engineering is very broad: from research labs, to financial institutions (banks, exchanges, clearing houses), to FinTech companies, and even regulatory bodies and governmental agencies.
For courses offered by the specialisation Financial Engineering, see the online studyguide.
Mathematics of Data Science
Data science is the interdisciplinary field that aims to extract information from large, possibly unstructured collections of data in a wide range of application areas. This specialization focuses on the mathematical aspects of data science, which includes probability theory, statistics, machine learning, deep learning and optimization. Not only can you choose courses on fundamental aspects of data science but there are more applied courses as well. There are courses that study data science from a stochastic, optimization or numerical perspective.
For courses offered by the specialisation Mathematics of Data Science, see the online studyguide.
Mathematics of Quantum Technology and Computation
MQTC equips the student with a broad range of state-of-the-art mathematical tools that are currently used in quantum technology and quantum computing, and are expected to underly future progress in the field. The various branches of mathematics that are represented in this specialisation (quantum algorithms, functional analysis, optimization) allow the student to choose an individual profile that fits his or her personal interests.
For courses offered by the specialisation Mathematics of Quantum Technology and Computation, see the online studyguide.
Partial Differential Equations
The specialisation Partial Differential Equations provides the mathematical tools required for the analysis of mathematical models. Such models are typically formulated as a system of coupled partial differential equations. Apart from very special cases, a closed-form solution cannot be given. Therefore, this specialisation focuses on the development of mathematical tools to study the properties of solutions, and methods to get approximate solutions and insight in the number and stability of these solutions. If you choose this specialisation you will learn techniques that come from the Approximation Theory, Dynamical System Theory, Fourier Analysis, Functional Analysis and Stochastic Analysis, to help you achieve these goals.
For courses offered by the specialisation Partial Differential Equations, see the online studyguide.
Stochastics focuses on the modelling and mathematical analysis of problems arising in science and engineering which are characterised by uncertainty. Randomness is an essential ingredient for many successful mathematical models. In this MSc programme students will become familiar with a wide range of techniques and theories underlying efforts to deal with randomness. The specialisation includes the following themes: Applied Probability, Statistics and Risk Analysis.
There is a huge demand for 'experts in randomness' in many different areas of society. Generally speaking, this specialisation prepares students well for employment in government or semi-government agencies, banks and financial institutions, industry, research laboratories and multinational companies.
For courses offered by the specialisation Stochastics, see the online studyguide.