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crop monitoring and decision-support systems for Controlled Environment Agriculture (CEA). This project focuses on the development, validation, and integration of non-destructive plant sensing
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, Applied Mathematics, Computer Science, Data Science, Mechanical Engineering, Physics, or a closely related quantitative field, completed by the start of the appointment. Strong theoretical and practical
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, conducts research at the intersection of theory-based modeling, predictive simulation, artificial intelligence, and plasma control. Group members have backgrounds in plasma physics, applied mathematics
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collaboration with CEA-Leti, Lynred, and other partners. The candidate will also be involved in the performance characterization and ground calibration of Near- and Short-Wavelength Infrared (NIR–SWIR) detectors