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theme of agriculture. Examples are Agricultural Science, Agricultural Economics, Statistics, Geoscience or related fields with a quantitative, empirical orientation and fundamental parts of agriculture
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knowledge of plant physiology, especially in phytohormone signaling and/or plant nutrition. Skills in statistics and the use of R are beneficial. You fit to us: If you are able to work collaboratively
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mathematics or a closely related field is required. Experience with some of the following topics will strengthen your application: statistical physics; critical phenomena; interacting point and particle
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models and methods for efficient semantic indexing, aggregation, linking and retrieval of comprehensive heterogeneous and distributed data sources. To this end, both statistical and linguistic analysis
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analyses, including 3D digital segmentation, digital measurement techniques, and geometric morphometrics Experience with statistical and phylogenetic comparative methods in R Proven ability to publish high
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the Research Group ”Stochastic Algorithms and Nonparametric Statistics” (Head: Prof. Dr. Vladimir Spokoiny) starting at June 1st , 2024. We are looking for: Candidates with a completed scientific university
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tool for agricultural datasets based on merging advanced statistics, machine learning and biophysical modelling regular interaction with the FAIRagro team to develop appropriate infrastructure
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-) ecology and zoology (preferably invertebrates or fish) Advanced skills in statistical analyses, preferably using R Strong track record of international publications Excellent written and oral