The mathematical statistics group of the Department of Mathematics and Computer Science is searching for an excellent candidate for a two-year Postdoctoral position. The
Mathematical Statistics group, which is part of the
Statistics, Probability and Operations Research (SPOR) cluster, focusses on developing novel statistical models and methodology endowed with theoretical guarantees, for the data-driven analysis of complex and high-dimensional systems. Our research topics range from heavily data-driven to fundamental and methodological aspects, including causal learning, dependence structure models, inference in complex networks, high-dimensional and non-parametric statistics and sequential decision making and data collection. The group also collaborates closely with the Teaching & Research Institute for Data Science Analytics (TRI-DSA).
As the successful candidate, you are expected to pursue independent research within your own agenda, provided these strengthen and complement the expertise in the group. As the position is not attached to a specific project there is considerable freedom to independently pursue your own research agenda, as long as it has a good embedding with the research activities of the group. The position comes with light educational duties for about 25% of your working time (this percentage includes preparation time as well). Your educational tasks might include tutorial sessions and office hours, grading exams and homework, student supervision, and lecturing.