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Vacancies PhD position on indirect combustion noise; Fluid Mechanics; CFD; Aeroacoustics Key takeaways Simulation-based development of indirect combustion-noise theory To remedy ineluctable
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that match surveillance intensity to individual recurrence risk. It pursues three objectives. Optimising follow-up. Determining when, for how long and in what form patients should be seen, and identifying
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-based follow-up strategies that match surveillance intensity to individual recurrence risk. It pursues three objectives. Optimising follow-up. Determining when, for how long and in what form patients
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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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Hydroinformatics – Uncertainty-Aware Optimisation for Robust Water Distribution System Operation The PhD candidate will develop uncertainty-aware, model-based multi-objective optimisation methods to support robust
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. Within this context, the role will contribute to assessing existing business processes and identifying opportunities for optimisation and simplification. Particular focus will be placed on reducing manual
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Post-harvest pathology Biomarkers, volatiles, and sensors Cold chains and refrigeration technology Data analysis and modelling (R, Python, CFD) Besides that, you have demonstrable experience in project
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measurements and/or Computational Fluid Dynamics (CFD) simulations. Specifically, you will assess where simplified assumptions in the model fall short. You will then train a machine learning model (such as PySR
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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