Concept

By the end of their training, doctoral researchers within KCDS will have a sound knowledge in their selected topics of applied mathematics (e.g. numerics, stochastics, differential equations), data science (e.g. methods and procedures for structure and pattern recognition, analysis and processing of large, partly unstructured data sets) and an application discipline. In particular, they will usefully supplement parametric models with data-driven methods. Graduates will be able to work out solutions to problems in a project-oriented manner and in cooperation with other scientists. They will be able to independently implement methods on large high-performance computing and data analysis facilities. They will be able to communicate their results to decision makers while outlining underlying assumptions and connected uncertainty. They would be competent in working within a legal and ethical frame. They will have the ability to acquire new methods and competence, both general and topical, in a self-reliant manner.