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programme aims to advance fundamental understanding of heat transfer and turbulence physics in wall-bounded flows through numerical simulations, data-driven modelling, and machine learning techniques. Key
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dimensionality reduction * development of optimization algorithms and numerical modeling procedures * development of simulation models using commercial packages (CST, ADS, HFSS, etc.) * writing technical reports
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PhenoRob experimental field sites, equipped with Eddy Covariance towers, to generate digital twins and quantify model uncertainties. For further information visit our website http://www.fz-juelich.de/ibg/ibg
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at the University of Southampton: https://software-oasis.com/ Our group is developing an innovative class of 3D climate models to explore the atmospheres and climates of Earth and other planets across the Solar
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Framework Programme? Horizon 2020 Is the Job related to staff position within a Research Infrastructure? No Offer Description Numerical and experimental modelling of reactive solute transport in unsaturated
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PhD Research Fellow in ML-assisted reservoir characterization/modelling for CO2 storage (ref 290702)
strong machine learning and numerical modelling background to add knowledge on the impact of geological heterogeneity and subsurface environments (e.g., depth, exhumation, temperature, pressure) to de-risk
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for trainees and staff. The ideal candidate will be an accomplished leader who models the highest standards of professionalism and integrity, has the vision to support and expand an existing interdisciplinary
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/Administrative Internal Number: 6791073 Postdoctoral Research Associate About the Opportunity The Postdoctoral Research Associate advances research in mathematical modeling, optimization, and stochastic analysis
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data in order to identify the different cooling stages and analyse the influence that different parameters may have on heat treatment D. Detailed numerical modelling of the heat treatment process to be
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structures like aircraft and vehicles. The research aims to develop a significantly more efficient numerical method. The candidate will thoroughly derive, implement, and validate novel models for crack