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Field
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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
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quality and quantity in agricultural systems. At the division, there are about 35 employees and around 20 PhD students. The current position is within the Remote Sensing and AI in Hydrology research group