Statistics and Applied Data Science (DSP StADS)

Sujet DSP


The Doctorate School Statistics and Applied Data Science (StADS) is an interdisciplinary “Meta” Research Training Group. It takes advantage of the particular site advantages and synergistic possibilities at the PLUS. There are few other locations where statistical-methodological competencies and expert knowledge span such a wide range of disciplines, combined with the desire of the individual scientists to establish sustainable interdisciplinary research collaborations centered around data science and statistics. StADS as a whole is more than the sum of its parts. Its goal is to provide deeper methodological focus, while maintaining a broad perspective.  
PhD students associated with StADS remain connected to their subject specific core training groups and attend the respective regular research seminars of their subject matter. Additional activities organized by StADS reflect the quantitative interest of the faculty members of this DSP. In other words, PhD students are brought to the international research boundaries of their disciplines, and StADS helps them on one hand to hone their quantitative skills, and on the other hand it acts as a catalyzer, enabling young scientists to enhance and apply their knowledge in an interdisciplinary setting.  
A major goal of StADS is to support interdisciplinary collaborations, resulting in joint publications, open source software, and grant applications. Among the StADS faculty are developers of statistical methods, as well as colleagues with vast experience in the application of statistical methods, spanning the most relevant software packages and programming environments (R, SAS, Stata). This allows for much flexibility in implementing and simulating statistical modeling in almost all empirical application areas.  
Participating faculty represent foundations and methodology of statistics and data science (Departments of Mathematics, Computer Science, Philosophy), life sciences (Departments of Cell Biology, Ecology and Evolution, Molecular Biology), and social sciences (Departments of Political Science, Sociology, Economics).