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for anomaly Detection and diagnostics: Leveraging state-of-the-art machine learning and deep learning models for automated fault detection, classification, and time-till-failure prediction. This will involve
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that transcends the boundaries of faculties and science disciplines. The PhD community is supported by the Doctoral Schools Ghent University and Gentse Pre- en Postdoc Raad . Psychosocial well-being at work and
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and science disciplines. The PhD community is supported by the Doctoral Schools Ghent University and Gentse Pre- en Postdoc Psychosocial well-being at work and ombudsperson Doctoral and other students
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visual behavior, visual circuit development, and automated behavioral assays. Methodologies include: Innate visual behavior assays using naturalistic visual stimuli (e.g. looming threats, prey-like
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visual behavior, visual circuit development, and automated behavioral assays. Methodologies include: Innate visual behavior assays using naturalistic visual stimuli (e.g. looming threats, prey-like
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here: https://edu.lu/wwpy7 Your role The successful candidate will join the SIGCOM Research Group, led by Prof. Symeon Chatzinotas, in collaboration with the Automation and Robotics Research Group, led
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farm layouts with high specific power density through the co-optimization of array design and control strategies. This project is a collaboration with CNR-INM Institute of Marine Engineering in Rome
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and a willingness to further develop those skills to automate your data processing and improve your own workflow efficiency are expected. You have a strong interest in catalysis and structure-function
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catalytic metals. These clusters will be deposited with high control over size and composition using cluster beam deposition on morphologically engineered TiO2 nanotubes. The most efficient catalysts will be
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platform. Initially, a black box deep learning approach will be implemented. However, due to the need for robustness, transparency, and explainability (e.g. for quality control across sectors), the research