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Field
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embedded in a multidisciplinary research environment combining expertise in machine learning (ML), numerical modelling, satellite remote sensing, and Arctic geosciences. The Centre is actively involved in
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managed boreal forest landscapes. The research will be done in terrestrial ecosystems. It aims to include experimental and observational studies (e.g. using field, lab, remote sensing data) along
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, using QUASI observations for validation and pushing the frontier of coupled modeling at submesoscales. Where, how, and with whom you’ll work Both PhDs will join the Geoscience and Remote Sensing
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of different remote sensing and mapped data, statistical modelling, mapping of fire risk and analyzing the effect of forest management for fire behavior. Considered remote sensing data includes airborne and
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, underwater gliders, micro-AUVs, and ship-based sampling), remote sensing products, and high-resolution numerical models. The work will improve understanding of coastal ecosystem variability, support better
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fuel structure, processing of different remote sensing and mapped data, statistical modelling, mapping of fire risk and analyzing the effect of forest management for fire behavior. Considered remote
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of everything we do. If you feel that this is the role you have been looking for and your skills and experience can make a real difference at LJMU, we look forward to hearing from you. LJMU is an equal
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engage to be a university where you feel at home and can flourish. We value different perspectives and qualities. We believe this makes our work more innovative, the TU Delft community more vibrant and
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from different geological disciplines and with prior experience of GIS/Remote sensing or programming is desirable. If your first language is not English, you will need to meet the minimum English
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skills in remote sensing, AI, ecological modelling, and policy engagement, working across disciplines and continents. The project includes an industrial supervisor to support non-academic training and