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both amplitude and phase information, but traditionally requires highly coherent light and controlled laboratory conditions. Recent developments in incoherent holography make it possible to capture
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, advanced packaging, backside power delivery networks, and chiplet-based architectures require new methodologies to model and optimize system behaviour beyond the traditional chip boundary. You will develop
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binder-precursor systems that support controlled bacterial colonization, and calcium carbonate and silica mineralization, while achieving relevant processing, microstructural and engineering properties
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models at the edge. While biomedical applications will be the primary focus of this work, the resulting ML models and hardware will be designed to be easily portable to a broad range of tasks based
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together with other energy assets, such as electrical boilers, within a Model Predictive Control (MPC) framework that optimally balances electricity and heat production. Within FLEX-SMR, this PhD focuses
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PROJECT DESCRIPTION Research aims at developing a wind-farm control emulator by coupling large-eddy simulations and aeroelastic turbine models with meso-scale weather models to run realistic wind-farm
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to better understand and control the manufacturing process so that small, precise, and reliable structures can be produced efficiently. These developments will contribute to the project's broader
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wind–wave flume. Measurements obtained from these controlled experiments will be used to validate and refine the numerical models. The validated models will then be used to identify critical wave
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methodology for both the integration architecture (combination of heat pump, thermal energy storage and possibly e-boilers), component sizing and control strategy will be developed. You will draw up a research