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of statistical data modelling is expected habitat and/or ecological modelling skills are desired knowledge of Structural Equation Models is advantageous experience in systematic data research is advantageous
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high-quality standards Confidence in the use of statistical modeling techniques and software (R or MPlus). This includes methods like panel data analysis, hierarchical models, spatial analysis
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statistical as well as communication skills are required. Working environment Apart from working closely with group members at the Kiel Institute, the successful candidate will liaise with external partners and
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, the ability to work with Stata (or other statistical software like Python or R). Tasks among others: General project assistance, general support in developing research articles and reports, literature research
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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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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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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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) sampling, above-ground carbon measurements, farmer surveys, focus groups, text coding and content analysis, statistics, GIS or land cover mapping experience working with agroecological data collection
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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