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a possibility of up to three years based on performance. The Davies Lab draws on the fields of community and ecosystem ecology, animal behavior, and remote sensing to explore multiple facets of animal
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continental forest datasets (e.g., ForestGEO, NEON, FIA) with remotely sensed datasets (including Lidar and satellite-derived datasets). This position is part of a federally-funded project examining impacts
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of climate change. The position is geared for a recent PhD graduate with interest in collaborating across disciplines, and expertise in remote sensing, spatial data analysis, machine learning and computer
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assessment to develop science-based solutions for climate and wildfire challenges. Full Job Description: Job Responsibilities Leading the analysis and interpretation of data from satellite imagery, remote
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engagement, and work collaboratively to useR scientific capabilities across ORNL. Collaborate with data scientists, machine learning scientists, remote sensing scientists, HPC engineers, Energy grid subject
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have an interest in ecological questions concerning infectious diseases of plants in natural and agricultural systems and experience working with remotely sensed data. Candidates are required to have a
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, Revisiting wind wave growth with fully-coupled direct numerical simulations, J. Fluid Mech. 951 [2022] A18); and/or iii) small-scale wave dynamics in the context of remote sensing and the effect of waves and
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of irrigation systems and sensors, overseeing irrigation activities, gathering plant and soil data, utilizing drones for remote sensing data acquisition, conducting laboratory analyses, performing comprehensive
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Qualifications Prior experience with learning technology Prior experience working at the intersection of Artificial Intelligence and Learning Science Prior experience with multimodal sensing (e.g., eye tracking
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and remote sensing; and lasers, optics, and applications. In 2015, the National Science Foundation selected the ECE department to lead the nation to scalable and sustainable change in engineering