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, ensemble Kalman filters, and physics-informed neural networks (PINNs) enforce conservation laws while fitting observations. The key is to apply the vast amount of physical insights developed in turbulence
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range (beyond 24 keV): measure and validate reference data in synchrotron beamtimes together with our international collaborators. Advance solid-state monitors: deploy new diamond sensors, model
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. For further information on the School go to https://www.unsw.edu.au/science/our-schools/chemistry The Senior Research Associate is a central role within the ARC funded Industry Laureate project, leading
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2-year postdoctoral position working on cutting-edge research in IoT sensor networks for critical infrastructure monitoring and mission-critical control systems. Expected start date and duration of
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the spatial reasoning capabilities of multi-mode large language models and hybrid AI systems combining artificial neural networks with symbolic AI. In-house research and development of one of these systems
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the spatial reasoning capabilities of multi-mode large language models and hybrid AI systems combining artificial neural networks with symbolic AI. In-house research and development of one of these systems
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related to project implementation details. Familiarity with electrical and power systems, energy storage systems, EV charging systems, test & measurement instruments, sensors/sensor networks, and PLC
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Posting Details Student Title Classification Information Quick Link https://chapman.peopleadmin.com/postings/38339 Job Number SE156824 Position Information Department or Unit Name Fowler School
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) for Fault Diagnosis of Energy Systems to support an EPSRC Supergen Network+ in Artificial Intelligence for Renewable Energy project funded through the University of Warwick. This is an exciting opportunity
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micro energy and smart sensing devices to tackle long-term challenges like “Healthier Citizens” and “Net Zero Human Impact.” She has collaborated for over 20 years with Aitor on projects related