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PHD DEVELOPMENT AND EXPERIMENTAL VALIDATION OF UNDERGROUND SAND-BASED THERMAL ENERGY STORAGE SYSTEMS
mechanical stability. You will support data acquisition and sensor setup for temperature profiling, model calibration and validation. You will apply multi-physical numerical modeling to develop 3D coupled
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model tests on granular flows.PhD position 2# is supported by an Advanced Grant of the European Research Council (ERC). The ideal candidate will focus on constitutive modelling and numerical simulations
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demonstrated for the first time at industrial scale. While the ICP principle has already been successfully tested in laboratory models, transferring it to industrial applications in the range of approximately 1
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operational challenges. You will model and conduct dynamic system simulations of full cooling systems (e.g. in Dymola) You will conduct experimental investigations focusing on the integration of active cooling
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Description Your Responsibilities Participation in one or more research fields of the institute: Material modelling of e.g. fresh concrete, soil, biological tissue (aorta, skeletal muscles) Numerical
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comprise all aspects of applied mathematics, from model development and mathematical analysis to numerical implementation and statistical estimation of models as well as software packaging. What to expect
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institutions. PhD topic: Numerical simulation techniques for the analysis of arrays of RTD oscillators Further details on the doctoral programme and the individual PhD topics can be found here . The aim
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engineering, environmental engineering) In-depth knowledge of: Geotechnics, numerical calculations with discrete element method, model tests, laboratory tests, geotechnical measurements, natural hazards, mass
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Research: Visual Exploration and AI Prediction Modeling of Real-Life, Multi-Modal Data” as a PhD-Position in machine learning. You will work alongside leading experts at the Computational Imaging Research