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and capabilities; leading the development of dedicated open science tools and virtual labs supporting atmosphere remote sensing and collaborative science; fostering international scientific
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phenomenology of land-, sea- and icescapes; and/or (3) remote-sensing-based machine-learning applications for archaeological modeling and survey. Importantly, this work will be carried out in close cooperation
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for other types of interaction and collaboration within the project, for example with colleagues from the Department of Geoscience & Remote Sensing at Delft University of Technology (TU Delft), and the
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& Design, Engineering Structures, Geoscience and Engineering, Geoscience and Remote Sensing, Transport & Planning, Hydraulic Engineering and Water Management. Click here to go to the website of the Faculty
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phenomenology of land-, sea- and icescapes; and/or (3) remote-sensing-based machine-learning applications for archaeological modeling and survey. Importantly, this work will be carried out in close cooperation
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and willingness to conduct and organize extensive ornithological fieldwork at a remote location; the willingness to travel internationally, to attend conferences and visit other institutes; A valid
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the following seven departments: Materials Mechanics Management & Design, Engineering Structures, Geoscience and Engineering, Geoscience and Remote Sensing, Transport & Planning, Hydraulic Engineering and Water
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vis-à-vis changing environmental/climatic conditions; (2) analysis of viewsheds and the phenomenology of land-, sea- and icescapes; and/or (3) remote-sensing-based machine-learning applications
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-wave inversion to make surface and subsurface moisture maps. The training programme includes engaging in advanced workshops and seminars focused on remote sensing and GNSS-R technologies and their
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languages such as Python. Experience with Geographic Information Systems (GIS) and remote sensing technologies will be considered an advantage. The successful candidate must be highly motivated, with a proven