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structural health monitoring of structures immersed in heavy fluids, by continuing to develop the “Modal Strain Energy” and “Matched Field Processing” methods for detecting and locating a potential defect in
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Mobasher. It involves a diverse range of activities including: structural and geotechnical modeling, machine-learning model development, structural sensing and health monitoring, conducting physical
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system automation. Investigate and improve human-machine interaction frameworks for construction operations, including robotics, sensor-based communication, and real-time monitoring. Publish research
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for real-time battery health monitoring and fault detection. Collaborate with embedded systems and hardware engineering teams to integrate AI models into the BMS. Optimize AI/ML pipelines for resource
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, machine-learning model development, structural sensing and health monitoring, conducting physical experiments, and validation of computational models. Required Qualifications: A successful applicant must
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frequency domain reflectometry (OFDR), and other technologies relevant to nuclear reactor structural health monitoring and maintenance. The candidate will be expected to install, configure, analyze, and
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, structural sensing and health monitoring, conducting physical experiments, and validation of computational models. Required Qualifications: A successful applicant must have a PhD in Civil Engineering
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, structural sensing and health monitoring, conducting physical experiments, and validation of computational models. Required Qualifications: A successful applicant must have a PhD in Civil Engineering
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. Analyze large datasets from battery systems to improve model accuracy and performance. Conduct research on predictive analytics for real-time battery health monitoring and fault detection. Collaborate with
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I - Physiology Posting Number req23566 Department Physiology Department Website Link https://physiology.arizona.edu/ Location University of Arizona Health Sciences Address 1501 N. Campbell Avenue