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Field
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: The scholar will lead research projects linked to detecting large-scale ocean biogeochemical changes using a combination of remote sensing, modeling and in situ observations. Specifically, the postdoc will use
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seven departments: Materials Mechanics Management & Design, Engineering Structures, Geoscience and Engineering, Geoscience and Remote Sensing, Transport & Planning, Hydraulic Engineering and Water
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an interdisciplinary, international research environment spanning ecology, remote sensing, socio-ecological systems, and climate adaptation. The researcher will work within a dynamic team committed to collaborative
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combining space-based remote sensing and modeling, it aims to better understand the evolution of forest fuels and their role in fire propagation. Tested on pilot forest areas (Centre-Val de Loire and Pyrénées
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project and will be genuinely excited to collaborate—both within the lab and with our broader network of partners. They will help strengthen the supportive culture of the lab, which values rigor, humor, and
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data for urban characterization. The work includes developing algorithms, performing large-scale analyses, and collaborating with partners across disciplines in remote sensing, urban studies, and climate
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interventions. Flexible hybrid working is possible: data analysis and statistical work can be done remotely, with regular on-site meetings for team collaboration and integration with clinical and imaging experts
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in international research visits if needed. We are looking for a highly motivated researcher with: A PhD in machine learning, computer vision, remote sensing, glaciology, climate science, or a related
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, atmospheric signals), data fusion across sensing modalities, and development of scalable machine learning pipelines. Work will be entirely computational and based in Seattle, with no field deployment
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sustainability. The candidate will develop and apply spatial analysis, remote sensing, and modeling to evaluate the technical, environmental, and socioeconomic implications of transitioning to resilient crops in