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through applications in the fields of data science (e.g., energy optimization of data analyses) and the Industry of the Future (e.g., the optimization of monolithic batch processes that are currently used
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(Destruction and Removal Efficiency) on targeted PFAS. 1.4. Interdisciplinarity aspects The topic requires an interdisciplinary approach, including knowledge of process engineering, thermodynamics and chemistry
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the intersection of different fields: innovation and entrepreneurship, and how to support them; open data/open innovation incentives and governance; data management and process modelling. The research will be
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availability. The research focuses on leveraging AI to automate and enhance these processes, reducing manual effort while ensuring robustness and scalability in dynamic IoT environments. 1.3. Considered methods
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broadcast communication protocols. Solid background in signal processing, probability, statistics, and optimization techniques. Experience with mathematical modeling of communication systems. Basic