The highly interdisciplinary Research Training Group aims at the solution of current questions in the areas of agricultural economics, genetics, ecology, econometrics and remote sensing by means of statistical methods, and at the development of the latter. It distinguishes itself through a structured graduation program, joint supervision, and a study program consisting of methodologically oriented lectures and interdisciplinary research seminars. Project will investigate the impact of different covariate scales on model choice and variable selection. Both model choice and variable selection are of high relevance when analyzing empirical data based on regression models but have been shown to be nontrivial tasks when covariates are measured on highly diverse scales. These problems are even more prevalent in complex regression models such as mixed models or geoadditive regression. In this project, the model choice and variable selection performance in such types of regression models will be studied and suitable strategies to overcome problems arising from the different covariate scales will be developed. The project will also include the application of the developed approaches in complex regression data arising for example in development economics and other areas of interest involved in the Research Training Group. The successful candidate will hold a M.Sc. degree or equivalent in statistics, mathematics, or in related fields with strong quantitative skills (including programming skills).
The University of Göttingen actively seeks to foster career opportunities for female scholars and therefore strongly encourages qualified women to apply. Candidates with disabilities who are equally qualified for the position will receive special consideration