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of Groningen, Nijmegen, Eindhoven and Tilburg). The PhD project in this vacancy contributes to the development of the above EmPowerED toolbox by developing simulation models for individual physical components
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-equilibrium conditions. The project is a UKRI/NSF collaboration with Virginia Tech, and the use of direct numerical simulation, modelling and analysis will be complemented with experimental data from
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synthesis over all relevant length scales (e.g. cutting-edge ab initio methods, atomistic simulation methods, multi-scale modelling, machine learning) • High resolution analysis, monitoring of chemistry
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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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of the world’s first open-access simulation platform for large-scale THz networks. Available PhD Position The position will include 18-month industrial secondments in the UK (Ranplan Wireless): UPI
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applications. Your main tasks: Develop and integrate degradation models for multiscale and multiphysics simulations of solid oxide cells Validate models using experimental data (e.g. IV curves, EIS measurements
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large erosion pit during a breach, iii) a flood wave much more powerful than water in terms of transport capacity and destruction of buildings. Analysis of the state of practices does not show a model
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degradation models for multiscale and multiphysics simulations of solid oxide cells Validate models using experimental data (e.g. IV curves, EIS measurements) Apply ML methods in combination with CFD
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evaluate earlier developed friction models and extend them to account for effects such as slip direction and temperature dependence. Implement the developed models in commercial forming simulation software
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of rainfall, drainage capacity, and 3D urban form on flood severity • Validate results with hydrodynamic simulations and 3D urban semantic models, benchmark against state-of-the-art methods, and publish in