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Field
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-based sensor data to enhance the prediction of peatland soil properties and functions. You will focus on leveraging machine learning/deep learning techniques along with explainable artificial intelligence
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independently. The workplace The Division of Automatic Control is successfully conducting research as well as postgraduate and undergraduate education within areas such as autonomous systems, complex networks
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) in the department and in the Great Plains IDeA-CTR network, and growing institutional strengths in AI, machine learning and clinical informatics. This is a unique opportunity to translate and expand
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sensor networks, robotics, energy, and Smart Cities • Network systems and economics, cooperative control and optimization, game theory • Distributed algorithms for decision making • Machine learning and
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National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | 3 months ago
Sentinel Site Network (CA-SSN), a partnership between the UC Natural Reserve System (UCNRS) and the California Department of Fish and Wildlife (CDFW). The post-doctoral fellow will conduct original and
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research network and seeks to recruit high-quality professionals to enhance its research- focused environment, based near Marrakech. About CRSA: The Center for Remote Sensing Applications (CRSA) is an
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, design and build a LoRa network infrastructure suitable for agricultural environments. Select appropriate hardware and sensors for data collection. Configure and deploy LoRa gateways and end devices
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participating in the training and management of PhD students. Solid-state spin- photon interfaces are central to emerging quantum technologies, such as optical quantum networks and quantum sensors. For example
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of improving human health. Aligned with Rutgers University–New Brunswick and collaborating university wide, RBHS includes eight schools, a behavioral health network, and five centers and institutes that focus
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Description The Jones Lab at Georgetown University uses innovative techniques to map greenhouse gas emissions both locally and around the world. The lab is actively engaged in sensor development, field work