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the optimization process. This project will play a key role in translating advanced CFD–ML methodologies into practical design and control strategies, helping unlock the full potential of urban wind energy
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institution of TUM Campus Heilbronn that uses data to answer relevant questions and solve real-world problems. It brings together fundamental, methodologically driven research in optimization, machine learning
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activities: · Understanding/simulating the diffusion paths and cavitation in thermoplastic liners. · Multi-physics simulation of the diffusion process in thermoplastic orthotropic composites
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IATE partners. Supervise the collection and processing of samples (fish feces, exposed microplastics). Develop and optimize enzymatic and chemical cleaning protocols for samples. Perform advanced polymer
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reactors available at the NTFM group Materials characterization and optimization of MOCVD/ALD processes to enhance the functional properties of ferroelectric and ultrawide bandgap (UWBG) materials. In-depth
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translatable novel cell-targeted nanotechnologies for target-specific drug/gene delivery and imaging applications to help diagnose and treat unmet medical problems in the areas of brain and eye diseases, and
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operations of chemical (mixing process in deep bed reaction systems), petroleum (oil-water separation systems), and biomedical industries (drug delivery encapsulating system) as well as in environmental
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, scientists with expertise in metabolic engineering, enzyme engineering, computational modelling, and process optimization will work together. By combining microbial strains with synthetic metabolism with
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use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our activities are experimentally driven and
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signal processing AI/ML for communication systems Self-supervised ML, meta learning PHY/MAC optimization of wireless communication systems Robust, reliable, or explainable ML Experience with large-scale