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to optimize the design and performance of floating breakwaters. Develop finite element models for stability assessment, structural integrity, and dynamic response of floating systems. 3. Connector Design Design
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Lexington, KY Grade Level 48 Salary Range $62,941-103,834/year Type of Position Staff Position Time Status Full-Time Required Education MA Click here for more information about equivalencies: https
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development, stack construction, system and component development, microscopy, spectroscopy) Presentation of findings at specialist conferences, publication in leading journals and active exchange with industry
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structural topology optimization vision-based structural health monitoring autonomous and drone-based infrastructure inspection and vibration monitoring Successful candidates must hold a PhD degree in Civil
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- or low-temperature) batteries, lithium- and/or sodium-based batteries, and solid-state batteries. Key Responsibilities: Design and execute experimental plans to develop and optimize next-generation battery materials
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include: Advising on and implementing responsive web marketing strategies, including front-end web development and updating website content to ensure optimal user experience and conversion optimization
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Mobility (IAM), considering ecological, economic, technological, and sociological factors. The RTG's structured PhD program aims to train young researchers in highly automated, networked mobility, featuring
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on the development of novel methods for the analysis and optimization of components and structures based on mathematical modelling and experimental investigations of phenomena that are highly interdisciplinary and
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for the captioned post. Duties and Responsibilities Conduct advanced research in structural health monitoring, including hardware development. Perform numerical studies and model testing. Analyze and interpret data
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Polytechnique de Paris. The group conducts research at the intersection of statistical learning, machine learning, and data science, with a strong focus on structured data, representation learning, and