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, sediment transport/deposition, landscape change); You enjoy working with large datasets and applying statistical analysis and modelling approaches; You use scripting/programming in your research (e.g. Python
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-have: You can independently and confidently analyze quantitative data and you can write reproducible code (for example, in R or Python). Good-to-have: You have worked with large-scale text data, natural
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R or Python). Good-to-have: You have experience working with large-scale text or visual data, or datasets related to history or culture. You tackle complex data challenges with curiosity and are
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programming and software development. Familiarity with Python and statistical computing libraries, like PyTorch or JAX, etc., would be preferred. You are a motivational teacher, with an encouraging teaching
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experience in quantitative methods, including automated content analyses and/or handling panel data Advanced analytical skills preferably using in R, Stata, or Python Excellent proficiency in English What do
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-up, crystallisation, and advanced analytical methods (NMR, IR, MS, PXRD). (Additional experience with reaction engineering, reactor optimisation, python for data analysis is considered beneficial but