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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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are you going to do? The project addresses a central question in mechanobiology: how do cells sense, encode and respond to mechanical cues? You will develop a quantitative and predictive framework
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Thermal Conversion and Storage group at the University of Twente, you will investigate CO₂ desublimation under controlled cryogenic conditions. The project is primarily experimental, supported by modelling
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, the effectiveness of Helix—and other advanced wake-mixing strategies—strongly depends on the accuracy of the wind farm models used to design and evaluate these control strategies. Improving the predictive capability
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of dynamical systems, control of complex and uncertain systems, motion control for high-tech systems, model predictive, networked, supervisory, neuromorphic, and learning-based control, cyber-physical systems
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Engineers usually want predictability. This project embraces chaos! – Excited about control theory? Then join us to build the math of chaotic sampling for greener and more secure control systems
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expand and improve an existing modelling framework to predict direct and indirect nitrous oxide and methane emissions from agriculture. You contribute to the following activities: Performing a SWOT
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, link ecological and EO data, and integrate your findings into models to predict ecosystem functioning in response to global changes and management interventions. You will learn how to publish your
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greenhouses than constructing detailed CFD models for each location. Key expected innovations in this project are expected to include a hybrid data-driven and model-based predictive control approach that uses
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ingredients, a process that is traditionally slow because each substrate–strain combination behaves differently. By applying machine learning to historical experimental data, we can predict high‑potential