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Field
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is to investigate the optimal configuration for utility-scale AWE farms, considering the physics, economics, and environmental impact. To determine the optimal scaling strategies for kite farms, a
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impact of energy generation. This PhD project is part of the MSCA Doctoral Network AWETRAIN (Airborne Wind Energy TRAining for Industrialization Network). Its objective is to investigate the optimal
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environmental footprint.In this context, the optimization of material recovery from end-of-life vehicle scrap is challenged not only by the heterogeneous and evolving nature of this scrap, but also by the diverse
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particular, we will use topology and shape optimisation methods to compute the optimal domain shapes that can stabilise solutions with desired/prescribed properties. We will use methods from inverse problems
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PhD student to establish recipes to provide post-plasma catalysis with different C2Hy distributions and different enthalpy content for optimization of post-plasma catalysis into C2H4. PhD candidate in
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reactor, with the goal of designing an optimized reactor for direct C2H4 production. Your colleagues: As a PhD Candidate, you will work in the plasmalab team in the Faculty of Science and Engineering
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of transverse transport on heat and mass transfer in a thermal arc plasma reactor, with the goal of designing an optimized reactor for direct C2H4 production. Your colleagues: As a PhD Candidate, you
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machine‑learning or data‑analytics tools High‑level programming skills (Python, R, Julia) to build, test, and optimize models of geochemical systems Interest in large‑scale computational simulations (e.g
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) Develop, optimize, and experimentally validate MC-based reliability solutions for multi-orbit systems compared to single-connectivity baselines Carry out research in other related areas Disseminate findings
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: Algebraic geometry and number theory Area 3: Stochastics and mathematical finance Area 4: Discrete mathematics and optimization Area 5: Discrete geometry Area 6: Numerical mathematics Area 7: Applied analysis