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Description Two PhD positions in atmospheric selenium research: field & lab analyses and process-based modeling We are seeking two highly motivated and curious PhD students to join the Inorganic Environmental
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Research Infrastructure? No Offer Description We are looking for a researcher to work on the finite element modelling of the interaction between textile materials (yarns and fabrics) and textile
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sciences, particularly in the domain of numerical weather prediction. On the one hand, state-of-the-art models such as GraphCast have demonstrated outstanding predictive skill. On the other hand, physics
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-of-year bonuses (8.3%), training and career development and sabbatical leave. Our individual choices model gives you some freedom to assemble your own set of terms and conditions. Candidates from outside
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-of-year bonuses (8.3%), training and career development and sabbatical leave. Our individual choices model gives you some freedom to assemble your own set of terms and conditions. Candidates from outside
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Infrastructure? No Offer Description Summary A fully funded PhD position (four years) is available for an Early-Stage Researcher in the area of additive manufacturing, with an emphasis on thermomechanical modeling
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nature (e.g. expressed by growth curves), can be derived from various markers, and can be obtained under various experimental conditions, these data form a huge analytical challenge. Furthermore
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Collaborative Doctoral Project (PhD Position) - AI-guided design of scaffold-free DNA nanostructures
nano-structures. In this project, we will combine numerical models, experiments, and artificial intelligence (AI) to guide the design of specific DNA nanoconstructs. The primary goal is to build an AI
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-plant-atmosphere relations applied to woody crops. Experience or knowledge on the use of crop models and remote sensing, particularly on the use of surface energy balance models to estimate ET Competence
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order to better understand, explain and advance society and environment we live in. Your role The PhD student will develop and apply computational multiscale models to investigate brain energy metabolism