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to join our research team investigating strategies to optimise tuberculosis (TB) treatment. The PhD project aims to improve treatment outcomes for people with TB by combining clinical research
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not produce powders with the quality required for advanced manufacturing. This PhD project aims to address that gap. You will develop and optimise routes for converting silicon-rich waste streams
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, Applied Physics, Process Technology, Civil Engineering or a closely related discipline) You have received training in multiphase flow physics, numerical methods, and computational fluid dynamics (CFD
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, numerical methods, and computational fluid dynamics (CFD), ideally complemented by application in your MSc thesis, research projects, or internships. Have excellent communication skills and command of English
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modelling for conversion and sorbent regeneration, in conjunction with another PhD student in the department who will perform CFD modelling and other researchers performing process system modelling within
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other partners within this project. In case a (moving of fixed) bed is chosen, a coarse-grained CFD-DEM model or an Eulerian model will be developed, possibly making use of correlations from particle
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to address that gap. You will develop and optimise routes for converting silicon-rich waste streams into high-purity powders. Using mechanochemical processing, you will investigate and control phase formation
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use. Research by our project partners will show how crops respond to microclimate setpoints based on detailed sensing data, and microclimate and crop models, obtained both through mechanistic and CFD
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Computational Fluid Dynamics (CFD) has become indispensable for aerospace design, many important problems—including high-fidelity flow simulations, uncertainty quantification, and multidisciplinary optimization
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; Proven competence on flow measurement techniques and PIV; Familiarity with optics, lasers, image processing and statistical data analysis Familiarity with flow modelling techniques (CFD) or machine