Description of Applied Stochastics
High-level training in statistics and the modelling of random processes for applications in science, business or health care.
For many complex systems in nature and society, stochastics can be used to efficiently describe the randomness present in all these systems, thereby giving the data greater explanatory and predictive power. Examples include statistical mechanics, financial markets, mobile phone networks, and operations research problems. The Master’s specialisation in Applied Stochastics will train you to become a mathematician that can help both scientists and businesspeople make better decisions, conclusions and predictions. You’ll be able to bring clarity to the accumulating information overload they receive.
The members belonging to the Applied Stochastics group have ample experience with the pure mathematical side of stochastics. This area provides powerful techniques in, for example, functional analysis, partial differential equations, geometry of metric spaces and number theory. The group also often gives advice to both their academic colleagues and organisations outside of academia. They will therefore not only be able to teach you the theoretical basis you need to solve real world stochastics problems, but also to help you develop the communications skills and professional expertise to cooperate with people from outside of mathematics.