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Field
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to predictably control and exploit the drop for useful tasks. Aims: Develop computational models to quantitatively predict the response of chemically active drops to the various physico-chemical stimuli
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with rapid PFAS breakthrough and as a consequence more frequent re-activation of activated carbon filters. The factors controlling breakthrough under realistic drinking water conditions remain
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investigate CO₂ desublimation under controlled cryogenic conditions. The project is primarily experimental, supported by modelling and data analysis. You will design, build and operate a cryogenic experimental
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. These sources, commonly known as inverter-based resources (IBRs), typically contribute limited fault current, and the phase of the injected current is dictated by their control systems, which can vary
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, control and predict learning in real time. This project addresses a fundamental question in neuroscience and provides advanced training in technologies relevant to Parkinson’s disease and psychiatric
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to grouted BHEs, ii) the influence of minewater circulation on thermal efficiency and heat plume evolution; iii) predicting flow pathways in a real-world case study emulating a system with high throughflow
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into high-purity powders. Using mechanochemical processing, you will investigate and control phase formation, particle size distribution, morphology, and flowability. You will then establish additive
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requirements for osteogenesis b) to dissect how targeted manipulation of the hydrogel affects mechanoregulation in human dental pulp stem cells, and c) to propose a computational model to elucidate and predict
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doctoral candidate on the MSCA-DN DETECTIVE project. For rapid control of virus outbreaks, fast availability of antivirals is a major bottleneck. In DETECTIVE, innovative models will be used for setting up
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precipitation, leading to scaling within reservoirs and production wells that reduces operational efficiency. Predicting where these processes will occur is a challenge because they are controlled in part by