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Position Information Position Information Working Title Assistant Geoscientist - Geospatial and Remote Sensing Scientist Department School of Natural Resources-0844 Requisition Number F_240063
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education and research in the areas of forest planning, forest remote sensing, forest inventory and sampling, forest mathematical statistics and landscape studies. The department is also responsible
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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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27 Apr 2024 Job Information Organisation/Company ISMAR CNR Sede Secondaria di Roma Research Field Environmental science » Earth science Researcher Profile Recognised Researcher (R2) Leading Researcher (R4) First Stage Researcher (R1) Established Researcher (R3) Country Italy Application...
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developing methods/tools that use multisource 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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: Experience with remote sensing analysis, geographic information system, or flood mapping and analysis. Experience with geospatial data management. Knowledge of cloud-based applications. Preferred
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in Europe; Analysis and integration of collected data and publicly available databases (e.g., FLUXNET, ICOS, remote sensing dataset); Co-supervise doctoral students and collaborate with other MPI and
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awarded 1 Eligible courses Any applicable Curtin HDR courses. Eligibility criteria Honours / Master’s degree or equivalent qualification in a relevant area (e.g., satellite ocean colour remote sensing
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Your Job: You will join the Simulation and Data Lab `AI and ML for Remote Sensing,` which aims to enhance visibility in interdisciplinary research between applications from remote sensing and large
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activity, and coastal protection benefits in the Caribbean. The postdoc will lead the development and application of a modeling framework to integrate remotely sensed datasets with coastal hydrodynamic