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ʻagreeable exotic worldʼ, all textiles enrobing bodies of the heavenly hosts harboured dynamic and flexible ontologies. Applying a multidisciplinary approach that cross-fertilizes art history, Kleiderkunde
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multispectral data, applying ML methods (e.g. XGBoost, LSTM, CNN). Run virtual “what-if” scenarios for nutrient, water, and light inputs to predict biomass, canopy, protein content and chlorophyll dynamics
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dynamics or climate dynamics, basic shell scripting, and python/Matlab/R or similar languages. Experience with “traditional” climate modelling, data-driven climate modelling, and working with large ensembles
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background in statistics is required, as well as experience in atmospheric dynamics or climate dynamics, basic shell scripting, and python/Matlab/R or similar languages. Experience with “traditional” climate
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worldʼ, all textiles enrobing bodies of the heavenly hosts harboured dynamic and flexible ontologies. Applying a multidisciplinary approach that cross-fertilizes art history, Kleiderkunde (visual
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from the hypothesis that before the conception of non-European lands as an ʻagreeable exotic worldʼ, all textiles enrobing bodies of the heavenly hosts harboured dynamic and flexible ontologies. Applying
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well as experience in atmospheric dynamics or climate dynamics, basic shell scripting, and python/Matlab/R or similar languages. Experience with “traditional” climate modelling, data-driven climate modelling, and