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Field
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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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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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-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
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element of embedded intelligence lies in the sensor's ability to self-calibrate and, in particular, to adapt its responses and models according to sensor aging and the (sometimes significant) variability
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of frictional behavior and advanced constitutive models to describe it. In this project, you will: Experimentally characterize ply-ply and tool-ply friction under a variety of processing conditions using our
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), IBPS, Sorbonne Université. The team possesses expertise in developing application-specific microfluidic models that integrate desired mechanical conditions of fluid flow and substrate viscoelasticity
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various components of the hydrological cycle (such as precipitation, evapotranspiration, runoff, and infiltration), forms the core of traditional hydrological modeling approaches. Although powerful