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. Approval of remote and hybrid work is not guaranteed regardless of work location. For additional information on remote work at Penn State, see Notice to Out of State Applicants . This is a term position
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communication skills. • Track record of conducting original research and publishing in peer-reviewed scientific journals. Preferred Qualifications • Experience in remote sensing or machine learning applications
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research in a wide range of academic fields, Ghent University is a logical choice for its staff and students. The MarSens (Marine Optics and Remote Sensing group, https://www.marsens-ugent.be/ ) investigates
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working at University of California Riverside More Jobs from This Employer https://main.hercjobs.org/jobs/21923204/postdoctoral-scholar-in-remote-sensing-of-biotic-stress Return to Search Results
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National Aeronautics and Space Administration (NASA) | Hampton, Virginia | United States | about 11 hours ago
in physical sciences or engineering-physics, experience with retrieving vertical profiles of constituents in the stratosphere with passive remote sensing techniques and excellent written and verbal
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analysis by integrating diverse datasets (e.g., in situ observations, remote sensing products, model simulations) to inform model development, calibration, and validation. Collaborate with a
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inclusiveness. This is why we warmly encourage qualified candidates from all backgrounds to join our community. We are seeking a talented and ambitious Postdoctoral Researcher in Remote Sensing of Peatlands
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networks), and the integration of these ground-based observations with state-of-the-art remote sensing information describing forest structure and function. The position will require computationally
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developing methods/tools that use multi-source remotely sensed data. The research aims to improve our understanding of the integrated functioning of continental surfaces and their interaction with climate and
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research on plant ecology in arid, semi-arid, and dry, sub-humid environments. The lab uses a variety of field ecological, remote sensing, and laboratory-based approaches to assess vegetation growth and