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Field
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and designing sustainable P2X value chains. As a PhD researcher, you will contribute to the new stack designs for high-temperature electrolysis and fuel cells (SOEC and SOFC). By combining numerical
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pressure and temperature levels; - Validate the numerical model of the complete system by comparison with experimental data; - Identify improvement strategies for performance and system robustness. Work
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research with numerical modelling. The group also has a strong track record in data-driven modelling of unsteady flows. This project explores how paired floating vertical-axis wind turbines can enable wind
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essential for transitioning to a carbon-neutral and energy-efficient society. Methane, a key component of natural gas and a by-product of numerous industrial processes such as naphtha cracking, presents a
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analysis, AI algorithm modeling, testing, and integration into functional systems within the project scope. Specifically, in activities related to behavior modeling from IoT device data, generative AI
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significantly slows down the development of new desirable nanostructures. In this project, we will combine numerical models, experiments, and artificial intelligence (AI) to guide the design of specific DNA
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problems, analyzing theoretical models of relativistic fermions in random potentials, advancing NPRG techniques for studying the interplay between interactions and disorder, implementing numerical
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attracting highly qualified talent. We look for researchers from diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security
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, multiphysics simulations, device implementation, and experimental validation. Key responsibilities: Develop theoretical and numerical models of piezoelectric energy harvesters under heavy-load conditions. Design
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by-product of numerous industrial processes such as naphtha cracking, presents a compelling opportunity. Current practices, such as combusting methane to sustain energy-intensive operations