Do you have a compelling and refreshing vision on statistical science – are you eager to move beyond traditional boundaries and conventional views, and lead the way in exploring emerging scientific challenges? We are looking for a full professor in Applied Statistics with a broad disciplinary expertise, strong mathematical background, and natural drive for pursuing applications.

The scientific direction of this full professor role is to develop statistical theory and data-analytic methods for the analysis of complex, large, and/or high-dimensional data sets. The focus of the research is to provide a more systemic view or a full breadth of all interrelationships of the collected data simultaneously, instead of determining inference or information on one specific feature of the data.

Specific topics of interest that would be related to these research goals include Bayesian analysis, causal inference, data harmonization, distributed analysis, network analysis, predictive analytics, spatial statistics, statistical learning, and survival analysis. Data collection techniques and design of complex studies, e.g., experimental design, nonprobability-based sampling, and surveys, are of interest as well.

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