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Field
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transfer. Fire observation systems. Interpretation of remote sensing data. Feather characterization. Modeling and automation of workflows. Robust processing of field measurements. Professional Experience
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will lead research at the intersection of crop-switching, environmental resilience, and agrifood sustainability. The candidate will develop and apply spatial analysis, remote sensing, and modeling
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of solution platforms for integrating spatial and temporal information, harnessing remote sensing data, using climate information, understanding fuel accumulation and running physics-based or data-driven
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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
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will lead research at the intersection of crop-switching, environmental resilience, and agrifood sustainability. The candidate will develop and apply spatial analysis, remote sensing, and modeling
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will lead research at the intersection of crop-switching, environmental resilience, and agrifood sustainability. The candidate will develop and apply spatial analysis, remote sensing, and modeling
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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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a public research laboratory which aims to better understand the functioning of continental surfaces and their interactions with climate and humans. Remote sensing is heavily used by Cesbio scientists
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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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the intersection of crop-switching, environmental resilience, and agrifood sustainability. The candidate will develop and apply spatial analysis, remote sensing, and modeling to evaluate the technical, environmental