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maintenance. Job Requirements Applicant Requirements Educational Background: A PhD degree in engineering, mathematics, or a related field, with a strong background in prognostics and health management (PHM
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degree in engineering, mathematics, or a related field, with a strong background in prognostics and health management (PHM) for engineering systems and structures, as well as expertise in machine learning
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sensors in composites. Strong mathematical background and experience with numerical methods for structural analysis. Proficiency in programming (e.g., MATLAB, Python). You have obtained your PhD degree in
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systems in port-cities and under threat from climatic and socioeconomic changes. You have an interest in conducting fieldwork, as well as bridging different theories and concepts, including urban metabolism
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respect to urban water systems in port-cities and under threat from climatic and socioeconomic changes. You have an interest in conducting fieldwork, as well as bridging different theories and concepts
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. Qualifications We are looking for a candidate with A PhD in Computer Science, Operations Research, Applied Mathematics, Mathematics, Engineering, or a related discipline. Strong programming experience, for example
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developers, electrical and mechanical engineers. Experience and strong understanding of machine learning algorithms, mathematical modelling, and applications of AI. Proficiency in Python, leading ML frameworks
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within a cross-functional team, including software developers, electrical and mechanical engineers. Experience and strong understanding of machine learning algorithms, mathematical modelling, and
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; experience with theory driven research with a clear eye for practical implications; a clear interest in collaborative interdisciplinary research; the ability to manage collaborations with partners outside
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composite propellers. Competence in the measurement and analysis of guided waves. Experience with embedded piezoelectric sensors in composites. Strong mathematical background and experience with numerical