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processes for virtual commissioning and optimization. Examine extensive heterogeneous data sets (including historical process data, sensor data, and laboratory findings) using advanced AI approaches such as
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Position Details Position Description Dr. Juming Tang’s group at the University of Washington has launched a new research program focused on developing novel sensors and AI tools to enhance the transparency
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, mineral, or biochemical analysis. •Use analytical equipment (pH meters, CO2 sensors, soil/root/plant sensors, chlorophyll fluorescence, etc.) and process samples using standard laboratory analytical
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and high-performance computing resources. The positions are part of the AI RF Sensors research group, which develops AI-driven methods for RF, microwave, and wireless technologies in close collaboration
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mesocosm experiment with precisely defined nutrient contents in the soil substrates, in which the sensor technology can be tested, as well as the continuous monitoring of the mesocosms with regard to plant
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out-couplers to interface with external light sources. This architecture will serve as a platform for developing both optical sensors and optical signal processors, leveraging existing integrated
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mechanism using surface on in-volume spatial variations. Structural health monitoring (SHM) and smart structures for composite infrastructures: Wireless surface gauges and integrated sensors, SHM/NDT/Inline
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of a next-generation turbidity meter (Arduino-based with radio communication to a central controller). * Develop and validate calibration methods for new sensors for turbidity and existing commercial
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Applying digital twin technology to ITS applications such as traffic management, vehicle routing, and infrastructure monitoring, as well as connected autonomous vehicles Integrating multi-modal sensor data
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Paulo Research Foundation, exhibits a strong interdisciplinary character, with activities involving remote sensing, artificial intelligence, and the use of sensors for real-time irrigation monitoring and