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Field
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/Biology Description: The Department is looking for a PhD student within the area of remote sensing of forest. Using remote sensing the PhD student will develop methods to quantify fire severity and analyze
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are rapidly evolving – ranging from remote sensing and automated sensors to genetic techniques and classical field-based inventories. This PhD project focuses on how biodiversity in forests can be measured
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analysis, statistical modelling or remote sensing experience with GIS, programming (R/Python) or handling large datasets demonstrated interest in method development or biodiversity research Great emphasis
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preferred) Experience with processing and analysing remotely sensed data Experience with GIS and spatial data analytical techniques Experience with carrying out fieldwork in related fields (e.g. Geography
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subject: Technology/Forest management/Biology Description: The Department is looking for a PhD student within the area of remote sensing of forest. Using remote sensing the PhD student will develop methods
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processes causing consecutive landslides will be undertaken. Training The individual joins a team of international experts who will support through training in remote sensing and GIS, field geomorphic
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to develop and apply advanced remote-sensing approaches and AI-assisted image analysis to investigate the distribution, diversity, and spatial dynamics of Antarctic lichen communities, thereby contributing
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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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hazards and assessing their risk for the society. At the same time, they are fully qualified users of remote sensing, GIS and statistictical software techniques that can be applied to geoscience and
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erosion and subsequent effect on land-to-lake dynamics using isotope tracer and source apportionment methodology at test sites in the Winam Gulf. (2) Explore use of remote sensing data and machine learning