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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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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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, these flows remain poorly understood. As a result, even the most basic properties cannot be predicted reliably. For instance, the best available models over- or underestimate the measured pressure drop in a
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Want to teach machines the mechanisms behind how the world changes — and build agents that act on them? Join us! World models are controllable, physics- and mechanism-grounded simulators of reality
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Explore trace element thermodynamics in high-temperature systems to control steel quality in the green transition—a PhD bridging experiments, modelling, and industrial impact. Job description The
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with a strong background in applied mathematics, control theory and/or optimization to apply for a fully funded 4-year PhD position in the Smart Manufacturing Systems (SMS) group at the Engineering and
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Welcome to Maastricht University! Join a public-private partnership working on the development of humin based recyclable networks for adhesive and composite applications. In this PhD project, you will
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Welcome to Maastricht University! Join a public-private partnership working on the development of humin based recyclable networks for adhesive and composite applications. In this PhD project, you
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suitable wireless link at any moment. In this PhD project, you will develop novel concepts for intelligent hybrid RF–OWC networks that optimize wireless service delivery in real time. Research topics include
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traffic demands increase, there is a growing need for innovative methods to continuously assess track condition and predict deterioration. This PhD project addresses this challenge by developing a novel