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multimodal data (video, self-report, physiological sensors, automatic facial recognition software) that examines CER in multiple contrasting contexts. And (3) Advance educational theory and practice by
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. To reach level-4/5 autonomy, we need teamwork: nearby vehicles, drones, and roadside units must co-perceive their environment, sharing and fusing complementary sensor views in real time. Yet raw video
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data, including TPMS (Tire Pressure Monitoring System), high-speed wheel encoders, CAN (Controller Area Network) data, accelerometers, and acoustics data. Understanding of sensor technologies and their
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University of Chicago, Pritzker School of Molecular Engineering Position ID: UofC -PME -POSTDOC [#30355] Position Title: Position Type: Postdoctoral Position Location: Chicago, Illinois 60637
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challenges and real-world impact. Project overview In recent years, generative neural network models for creation of photo-realistic images have become increasingly popular. Their training results in a low
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of GPP (gross primary production) to a nutritional stress for K (Cornut et al., 2022) The overall objective of this postdoc project is to improve our knowledge of nutritional dynamics in forest ecosystems
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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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of GPP (gross primary production) to a nutritional stress for K (Cornut et al., 2022) The overall objective of this postdoc project is to improve our knowledge of nutritional dynamics in forest ecosystems