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their analytical and numerical predictions with available experimental data. Applying the developed models to provide quantitative understanding of how the spatiotemporal profile of corticoids and androgens varies
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. The research in the PhD project will focus on core spatio-temporal machine learning method development, including: generative models for grid-based and particle-based spatio-temporal data; controlled generation
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by comparing their analytical and numerical predictions with available experimental data. Applying the developed models to provide quantitative understanding of how the spatiotemporal profile
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-temporal machine learning method development, including: generative models for grid-based and particle-based spatio-temporal data; controlled generation methods for data assimilation; and graph-based multi
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carried out in a controlled cooling carousel E. Experimental validation of the numerical model of the heat treatment process for controlled air cooling in a carousel F. Generation of a numerical prediction
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-focused, will directly support advanced flood risk modelling, hydrological predictions, and adaptation planning. As the student, you will gain expertise in climate extremes, data science, and hydrology
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the various phases of silicon in various 3D stress configurations. A predictive model should properly account for the complex physics, damage and fracture. The loading conditions in contact and scratching
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along with physiological and behavioural data of test drivers and build explainable predictive models out of it. The research team spams Luxembourg, Europe and the USA and will make use of world-leading
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Inria, the French national research institute for the digital sciences | Toulouse, Midi Pyrenees | France | about 1 month ago
(e.g. ONERA M6 wing, of full wing-bod models as the CRM or XRF1), especially in the transonic regime, the impact the geometrical accuracy on the correct prediction of shock structures and boundary layer
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controlling their noise is critical. This PhD focuses on airborne noise source localization in urban environments, enabling quiet air mobility. Job description The rapid growth of air mobility operations