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management platform that connects institutes to facilitate a rapid and efficient exchange among experimental and computational groups Devising an approach in invertible predictive modeling that links
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: Prof. Dr. Steven Travis Waller, Chair of Transport modeling and simulation, and co-supervised by at least one additional professor, plus an international tutor of the CRC Requirements: excellent
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responsibilities: To carry out and complete your own research towards a doctoral degree. Design, run, and analyse equilibrium simulations with a coupled Earth-system model of intermediate complexity to investigate
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its rich information content, conventional analysis methods have not yet fully realized its potential. This research project aims to develop a robust AI foundation model based on modern Transformer
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for climate-positive and CO2-negative processes. What you will do Optimization of the pilot plant for the combustion of solid fuels (biomass, waste) with oxygen and subsequent CO2 capture Development of models
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experience growing, managing, and phenotyping plants in the field and greenhouse. You have experience using modern approaches in root phenotyping, image analysis, or simulation modeling to understand
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on mesoscale fluid dynamic simulations, microclimatic and turbulence modelling procedures in urban environments shall be performed. Subsequently weather-and turbulence-related limit values shall be formulated
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approaches in root phenotyping, image analysis, or simulation modeling to understand the functional roles of plant roots in agroecosystems. You have excellent communication skills and will to collaborate with
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the comprehensive field of Earth System Modelling, with emphasis on the interactions between the natural and the human systems. The scientific subject is the development, application and evaluation of a hierarchy of
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the field and greenhouse. You have experience using modern approaches in root phenotyping, image analysis, or simulation modeling to understand the functional roles of plant roots in agroecosystems. You have