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the nitrogen balance through careful measurements of N inputs and N outputs under different treatments and weather conditions. The research will utilize graphene sensors to measure N losses through the soil
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through the use of mobile games and wearable sensors, which offer an opportunity to collect complex, continuous behavioral and physiological data from individuals over long (e.g., 6 months) periods of time
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of scientists and researchers in an effort to research transcription factor-based sensors for waterborne toxins of interest. High-throughput cell-based and cell-free screening approaches, along with
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on reducing acute mountain sickness, another involving testing the reliability and validity of novel wearable sensors to detect oxygen saturation, a third involving the prediction of heat stroke and a fourth
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like convolutional spectroscopy, drone-mounted sensors, and experiments to understand the impact of aerosols on thermal blooming, cloud transmission, and RF/microwave link performance under varying
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of the following areas would be advantageous: deep learning, large language models, crop models, environmental models, or similar, UAV or satellite derived image or sensor data. Stipend $60,000.00 – $85,000.00
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plant physiological sensor systems to monitor environmental and crop dynamics. Strengthen data management and analysis competencies through the collection, processing, and management of large
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. Students will collaborate closely with laboratory scientist mentors and technical staff on a variety of seasonal experimental activities. Opportunities may include helping with low-voltage sensor calibration
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tolerance for varietal selection. Learning Objectives: Participant will gain laboratory, field, and programming skills to develop the digital twin and other AI models using ground and above-ground sensors and
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using sensors, data loggers, and thermal images Lab experiments examining how nutrition affects performance and physiological traits Field experiments quantifying behavior of insects Mentor(s): The mentor