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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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of microbiology and laboratory automation. We are looking for a highly motivated PhD candidate with a strong engineering mindset and a keen interest in AI, automation and microbiology. Prior experience in
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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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of microbiology and laboratory automation. We are looking for a highly motivated PhD candidate with a strong engineering mindset and a keen interest in AI, automation and microbiology. Prior experience in
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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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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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properties of the cluster-substrate system using an automated photocatalytic gas test setup for CO2 photoreduction available at A-PECS. Importantly, the PhD candidate will thus receive a joint PhD degree by
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Networks, and ICT Services & Applications. Your role The SnT Automation & Robotics Research Group is hiring a motivated PhD candidate for the bi-national project DOMINANTS (Dexterity-Oriented Methodology in
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, such as control and automation, mechanical engineering, robotics, electromechanical or mechatronics engineering. Ideally candidates have experience in system identification, theoretical and numerical