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/ Medical Sub-Speciality Location Tucson Campus Address Tucson, AZ USA Position Highlights This Research Professor will develop and maintain an externally funded research program in remote sensing
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scale is based on the analysis of seasonal patterns at the European scale of the remotely sensed spectral index (PPI) at multi temporal scale in wild fruit stands. In-situ phenotyping of CWR at the tree
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at the policy–academic interface. This position is ideal for an early- or mid-career researcher with experience in GIS or remote sensing who seeks to apply and expand their expertise in a fast-paced
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and human activities. CESBIO scientists make extensive use of remote sensing technologies to monitor environmental changes across spatial and temporal scales and to develop models that address key
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YOUNG RESEARCHER IN THE FIELD OF EARLY DETECTION OF THE HEALTH STATUS OF PLANTS USING REMOTE SENSING
Mathematics » Statistics Geosciences » Other Technology » Remote sensing Engineering » Agricultural engineering Computer science » Programming Computer science » Informatics Computer science » 3 D modelling
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DC-26094– POSTDOC/DATA SCIENTIST – AI-DRIVEN CLIMATE RISK MODELLING AND EARLY WARNING SYSTEMS FOR...
: https://www.list.lu/ How will you contribute? You will be part of LIST’s Remote sensing and natural resources modelling group Embedded in the Environmental Sensing and Modelling (ENVISION) unit
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-technologies ) group, coordinated by Arianna Traviglia. This group focuses on Cultural Heritage Technologies: Remote Sensing Technologies. Your activity will comprise State-of-the-art models report preparation
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Ministero dell’Agricoltura, della Sovranità Alimentare e delle Foreste (Soggetto attuatore ISMEA) | Italy | about 19 hours ago
evaluating the productive and qualitative responses of crops affected by the application of such residues both from proximal and satellite surveys (remote sensing) Where to apply Website https://www.unifg.it
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the long term. Is Your profile described below? Are you our future colleague? Apply now! Education PhD degree in remote sensing, preferably with a doctoral thesis on RTM inversion or deep learning in remote
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or orbital remote sensing. Individuals who apply remote sensing techniques to the study of ongoing tectonic processes such as earthquakes, volcanoes, and associated hazards on societally relevant timescales