德国研究培训集团统计学博士后职位
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The highly interdisciplinary RTG “Scaling Problems in Statistics” studies scaling problems in the areas of agricultural economics, ecology, econometrics, genetics, remote sensing and statistics with the aim of developing, extending and applying general statistical methods that are designed to account for different notions of scale. Specifically, methods from spatial statistics, mixed models and distributional regression are in the focus of the statistical developments.The successful candidate for this postdoc position should supplement the methodological competencies of the RTG in either of these areas.
The RTG involves working groups from Agroecology, Agricultural Economics and Rural Development, Animal Breeding and Genetics, Ecosystem Modelling, Forest Inventory and Remote Sensing, Genetic Epidemiology, Mathematical Stochastics, Statistics and Econometrics. For more
information, visit www.uni-goettingen.de/rtg1644
Successful candidates hold an excellent Ph.D. or equivalent in statistics or mathematics with a specialization in statistics and should have a strong background in statistical modelling, ideally with a focus on spatial statistics, mixed models, distributional regression or computational statistics.They should have demonstrated their ability for interdisciplinary collaboration with applied researchers and a corresponding track record of publications. The willingness to contribute to the teaching program of the Research Training Group and to offer consulting for Ph.D. students of the RTG is further required. Very good command of English is a prerequisite.
The University of Göttingen is an equal opportunities employer and places particular emphasis on fostering career opportunities for women. Qualified women are therefore strongly encouraged to apply as they are underrepresented in this field. Disabled persons with equivalent aptitude will be favored.
To apply for this position, please send your application including motivation letter, CV, certificates, two reference contacts, and a short exposé with an outline of your research interests and ideas as one single PDF file.
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