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future is a thorough understanding and assessment of the thermo-physical properties (e.g melting temperature, heat capacity, density, viscosity, thermal conductivity) of the molten fuel salt during reactor
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models are required. As a PhD in this project, you will develop metamodels that are fast enough to be used for design optimisation. The metamodels will be trained based on readily available validated DEM
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Challenge: Generating realistic bathymetric maps at a large scale using satellite images and advanced machine learning methods. Change: Incorporating physics into satellite-derived bathymetry
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bioprocesses still have. This effort includes quantifying the impact of various process routes as well as creating micro-organisms (or consortia thereof) that can deal with new feed stocks or produce more
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this PhD theme, you will consider ways of increasing students’ responsibility toward their learning. You will explore the current landscape of engineering education practices with regard to the role
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performance, we will pioneer novel physics-informed machine learning algorithms to formulate an optical link performance map. This groundbreaking project comprises two PhD positions and one postdoc position
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The Analysis research group within the Delft Institute of Applied Mathematics at TU Delft is offering a full-time PhD position in the area of Numerical Methods for Stochastic Differential Equations
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for this PhD position you should have: A Master's degree in electrical/electronic engineering, computer science, physics, mathematics or other related fields. Knowledge and interest in radar signal processing
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We seek a motivated PhD student to work on a 4-year NWO funded project called DARE (Distributed and Adaptive Radar for Enhanced Sensing and Classification). The goal of this project is to work
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green propellants, produced in orbit through an innovative conversion process applied to liquid water. More specifically, the areas under the direct responsibility of TU Delft will be: the development and