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infrastructure, mobility, and energy management. Integrate real-time data from sensors and IoT devices to develop dynamic models. Model complex interactions between physical systems (infrastructure) and digital
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close-to-field conditions, and (ii) a fully autonomous phenotyping robot, Phenomobile.v2+, equipped with a set of sensors (LiDAR, RGB, IR, and Spectrometer) that enable advanced plant measurements
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of the BMS in lithium-ion batteries, including sensors, actuators, and controllers. In our facility, we are establishing a research unit focused on developing the necessary hardware and software components
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sensor data, public databases, and GIS. Predictive Modeling:Design predictive models to evaluate the impact of urban and environmental policies on public health. Interdisciplinary Collaboration:Collaborate
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set of sensors (LiDAR, RGB, IR, and Spectrometer) that enable advanced plant measurements, that allow us to assess plant’s water budget in response to abiotic stress and nutrients’ application
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. Required Qualifications : Doctorate: A PhD in Industrial Engineering, Environmental Engineering, Waste Management, Data Science, or a related field. Modeling Expertise: Proven experience in designing
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, seeks a postdoctoral candidate in wireless sensor networks and the Internet of Things. The successful candidate will join the group of Prof. Youssef Iraqi. Context Wireless sensor networks (WSNs) and
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and sustainable sensor systems for industrial applications. This position offers an exciting opportunity to contribute to cutting-edge research in the field of sustainable materials to develop promising
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partners, and other research institutions; Publish research findings in peer-reviewed scientific journals. Qualifications: PhD in geology of igneous rocks or equivalent, obtained within the past two years
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sensing, IoT sensors, and climate models. Design and implement deep learning models for forecasting extreme weather events such as floods, droughts, and heatwaves, integrating probabilistic approaches