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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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Observation data including Satellite Remote Sensing together with Soil and geospatial datasets. Salary Post-Doctoral Researcher, Level 1 (2025): €45,847 p.a. (1 point - with increment) Appointments will be made
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Inria, the French national research institute for the digital sciences | Montpellier, Languedoc Roussillon | France | 3 months ago
postdoctoral researcher to work on the interpretability and explainability of Vision-Language Models (VLMs) for remote sensing applications, with a specific focus on Sentinel-2 data. This research aims
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North Carolina A&T State University | Greensboro, North Carolina | United States | about 2 months ago
/Administrative Internal Number: 37162 Description: This is a full-time Postdoc position to develop the remote sensing data fusion to automatically extracting spatio-temporal features using integrated data-driven
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at very high spatial resolution. The candidate will collaborate closely with the Remote Sensing and Hydrology lab and the Rutgers Infrastructure Resilience Group. Both groups involve a number of research
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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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modeling, AI-driven simulations, optical remote sensing and biogeochemical modeling to predict seagrass distribution under various climate and nutrient scenarios. SEAGUARD aims to provide science-based
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students and contributing to educational initiatives. Experience with remote sensing, GIS tools, and image analysis techniques is an advantage, as is knowledge of genetic methods (e.g., SNP-based data
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or related fields programming experience in Python or extensive experience in another high-level programming language is a prerequisite experience in geospatial data science, remote sensing, GIS, and open
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proficiency in languages such as R and Python. Experience in GIS, remote sensing, and processing projected climate data. Proven ability to manage multiple tasks effectively, work collaboratively in team