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Department of Forest Resource Management The Department of Forest Resource Management conducts education and research in the areas of forest planning, forest remote sensing, forest inventory and
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Dipartimento di Ingegneria dell'Informazione - Università degli Studi di Padova | Italy | about 2 months ago
developing prototypes of enzymatic chemical biosensors, contributing to the creation of metasurfaces operating in the microwave range for remote sensing applications. Given the characteristics of the position
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of cultural heritage. Remote sensing, and in particular Synthetic Aperture Radar (SAR), provides valuable insights into vegetation structure, soil roughness, and soil moisture. The Copernicus program of
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at their assigned camp and participate in onsite pre-camp training. Apprentice Faculty must have completed at least one year of a master’s or PhD program in mathematics or a related field. Room, board, and round-trip
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cases of next generation wireless communications systems. For details, you may refer to the following: https://wwwen.uni.lu/snt/research/sigcom We're looking for people driven by excellence, excited about
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of hire. The required degree must be in the fields of agricultural science, machine learning, remote sensing of environment, ecosystem analysis, micrometeorology, quantitative modeling, or relevant fields
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rolling basis with start dates as early as 1/1/2026 and as late as 3/1/2026. Group or Departmental Website: https://simpsoba.su.domains/ (link is external) How to Submit Application Materials: Please upload
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funded by the Grains Research & Development Corporation (GRDC). The project is led by CSIRO with the University of Sydney leading the component on the assessment of soil health using remote sensing
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to interpret remote-sensing observations of icy moons. You will join an interdisciplinary and international team that integrates laboratory astrochemistry, spectroscopy, quantum chemistry, radiative-transfer
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potentially using a mix of remote sensing, vegetation/habitat data, field data, and camera trap data to model connectivity for large mammal species and/or migratory birds. Expected project outputs will include