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of mathematical modeling and data analysis. Experience of programming languages and tools commonly used in biophysical or agricultural modeling (e.g., Python and R). Familiarity with food system resilience
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area “statistics to serve society” which focuses on developing statistical methods and software for the analysis of large and complex collections of data. The PhD student(s) is planned to be connected
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