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Field
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, a large initiative funded by the Danish Ministry of Foreign Affairs and managed by Danida Fellowship Council. Ethio-Nature aims to optimize the use of machine learning and remote sensing to site
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spatial analysis and vulnerability mapping for flood-prone regions. Utilize remote sensing and geospatial tools to analyze flood exposure and mitigation strategies. Support the ClimateIQ project by
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, multi- layered spatial data sets (e.g. Remote Sensing and GIS), and contributing to the growth of the interdisciplinary Integrated Coastal Studies Program, which focuses on issues related
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that use multi-source remotely sensed data. The research aims to improve our understanding of the integrated functioning of continental surfaces and their interaction with climate and humans, with emphasis
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engineering, earth science, computer science, or related field required. A PhD specializing in glacier modeling, remote sensing, and/or statistics preferred. Python coding experience preferred. Strong
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. Contribute to the supervision of master and PhD students. Qualifications: Ph.D. in Earth Sciences, Remote Sensing, Physics, Applied mathematics, or related field. Strong background in land surface modeling
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for remote sensing data analysis.- Satellite image time series processing.- Oral and written communication in English and French. Savoir faire technique : - Working in Linux OS and HPC. - Advanced python
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in the case study regions support the PhD student in the project support integration of remote sensing based output into implementation in decision-making tools support project coordination and
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peer-reviewed journals and present results at conferences and workshops. Contribute to the supervision of master and PhD students. Qualifications: Ph.D. in Earth Sciences, Remote Sensing, Physics
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has also involved development of remote sensing tools for mapping agricultural diversification practices. The postdoc will join DSE's vibrant multidisciplinary cohort of postdocs, data scientists, and