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Three PhD positions at TU/e in collaboration with Canon Production Printing, combining polymer science, rheology, and computational modeling to create the inks and coatings of tomorrow. Information
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strong focus on the generation and evaluation of structured synthetic health data. You will also explore the application of large language models (LLMs) to healthcare data and terminology systems. Your key
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and macroscale structural dynamics. As a PhD candidate, you will focus on the identification and modeling of friction damping and energy dissipation in assembled structures. Your work will combine
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structural modeling, machine learning, and competitive intelligence to infer demand using partial or aggregated signals. While early results are promising, important questions remain: Which partial data is
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specially designed test structures and new tunnelling devices realised in advanced CMOS. Based on a thorough literature review and the outcome of this research, the main challenge will be to (co-)develop
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boundaries of system-level modelling, analysis, design, exploration and synthesis beyond the current state-of-the-art? Or are you curious to learn more about the application of AI for system diagnostics and
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specially designed test structures and new tunnelling devices realised in advanced CMOS. Based on a thorough literature review and the outcome of this research, the main challenge will be to (co-)develop
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computational facilities. The powerful computational facilities enable us to develop advanced numerical models. The Department of Engineering Structures focuses on the development of resilient, smart and
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for pavement lifetime prediction, primarily in Dutch conditions. Foreseen challenges include data harmonization, key relationship extraction, scalability, metadata structuring, predictive modeling, and data
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to organ-level outcomes. Your research will clarify how dicarbonyl and AGE (advanced glycation end-product) stress contribute to age-related changes in cardiac structure and metabolism and identify potential