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central controller). ● Develop and validate calibration methods for new sensors for turbidity and existing commercial sensors. ● Explore high-frequency turbidity monitoring as a tool for assessing
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advanced data on nature and biodiversity (derived from AI-supported monitoring and analysis of sources such as satellite imagery, acoustic sensors, and camera traps) can inform spatial planning and decision
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, and iterate the design 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
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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description AI-enabled polymer monitoring via multi-sensor intelligent non
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wastewater. This includes sensors and sensor networks for detection of these targets and testbeds for the validation of technologies developed. INSTITUTIONS HIRING: Northwestern University University
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for geometry assurance – integrating live sensor geometric sensor data with simulation for real-time control and adaptive assembly. This builds on existing work within the group on digital twins for geometry
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project that involves designing microfabricated biomedical sensors and the readout circuitry for recording electrophysiology and electrochemical signals from biological samples. The overarching goal
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sensor geometric sensor data with simulation for real-time control and adaptive assembly. This builds on existing work within the group on digital twins for geometry assurance. AI for automatic tolerance
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candidate has experience with two or more of the following points. Reactor operation (lab- or pilot-scale) Operation and maintenance of control systems and sensors Proficiency in process modelling and
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orbital sensors (e.g., ECOSTRESS, VIIRS, Landsat/MODIS) to build pre- and post-fire structural and functional diagnostics. Develop recovery chronosequences from multi-sensor time series and quantify