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is currently building and commissioning a network of calibrated multi-sensor observatory-class systems, and developing novel machine learning methods with the aim of collecting science-quality data
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conventional, frame-based sensors in comparison to event-based sensors, which are more commonly associated with neuromorphic computing. This work will support mission design decisions regarding the suitability
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systems (ITS). In particular, the successful candidate will conduct cutting-edge research in: Developing physics-informed neural networks (PINNs) for complex dynamical systems modeling and observer design
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-generation Intelligent Sensing and Communication) systems can expand coverage with higher network efficiency, lower cost, and lower power consumption compared to the existing technologies. In FR2(mmWave) and
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Republic of Korea | 13 days ago
-generation Intelligent Sensing and Communication) systems can expand coverage with higher network efficiency, lower cost, and lower power consumption compared to the existing technologies. In FR2(mmWave) and
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and sustainable sensor systems for industrial applications. This position offers an exciting opportunity to contribute to cutting-edge research in the field of sustainable materials to develop promising
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different data collection methods and sensors used to gather road condition data, including TPMS (Tire Pressure Monitoring System), high-speed wheel encoders, CAN (Controller Area Network) data
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About the Role This Postdoctoral Research Associate (PDRA) position is part of an exciting EPSRC-funded programme, "Enabling Net Zero and the AI Revolution with Ultra-Low Energy 2D Materials and
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of Standards and Technology, The Department of Energy, and the National Aeronautics and Space Administration. Development and application of quantum sensors is an area of research in which maintaining a position
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-time data for dynamic urban system modeling. In-depth knowledge of IoT sensor networks for collecting and analyzing urban data (traffic, energy consumption, environment). Strong skills in integrating IoT