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Field
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: Biodiversity is a fundamental prerequisite for the ecological functioning, resilience, and long-term sustainability of forests. At the same time, new methods are rapidly evolving – ranging from remote sensing
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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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worldwide. Research methodology The researcher will combine existing landslide inventories with new remote sensing observations to build multi-year databases of landslide occurrences and control factors (i.e
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planning, forest remote sensing, forest inventory and sampling, forest mathematical statistics and landscape studies. The department is also responsible for the implementation of the ongoing environmental
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role in shaping the research direction by selecting study regions, refining analytical approaches, and integrating methods across atmospheric science, remote sensing, and epidemiology
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quantum computing as well as experience with cryogenics, signal delivery, microfabrication, materials optimization, and microwave control are highly preferred qualifications Please feel free to apply
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will develop and evaluate new approaches to predicting current and future population exposure to such hazards by combining numerical modelling and remote sensing of river migration, with machine learning
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remote sensing data. Your job As a PhD candidate, you will study how the rapid thinning and loss of sea ice in the Arctic Last Ice Area, north of Greenland and Ellesmere Island, affects surface melt and
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venues Prior experience with agricultural applications or remote sensing We Offer A fully funded PhD position for 3 years (TV-L E13) Opportunity to work on real-world agricultural challenges with
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of cultural heritage. Remote sensing, and in particular Synthetic Aperture Radar (SAR), provides valuable insights into vegetation structure, soil roughness, and soil moisture. The Copernicus program of