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Postdoctoral Research Associate in Forest Resilience, Climate Change, and Human Health in the Amazon
illnesses. The post holder will also co-supervise a PhD student who will be involved in the same project. This is a highly interdisciplinary project combining forest ecology, remote sensing, machine learning
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Position Highlights We seek an early career scientist with background in ecohydrology, numerical modeling and/or remote sensing to fill a position as Postdoctoral Research Associate at the Department
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USA Position Highlights We seek an early career scientist with background in ecohydrology, numerical modeling and/or remote sensing to fill a position as Postdoctoral Research Associate
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these changes, identify their causes and describe their impacts on biodiversity and ecosystem services. To do this we use a combination of diverse methods, from empirical research to remote sensing and simulation
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Postdoctoral Research Associate in Forest Resilience, Climate Change, and Human Health in the Amazon
holder will also co-supervise a PhD student who will be involved in the same project. This is a highly interdisciplinary project combining forest ecology, remote sensing, machine learning, epidemiology
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should have a PhD (or close to completion) in Physics, Planetary Sciences or Earth Sciences. It will be an advantage to have experience in remote sensing, analysis of thermal data, thermal modelling
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(35 hours per week) offered on a fixed-term contract for 11 months (up to 14 months if part-time), starting in September/October 2025. Part-time, flexible, and remote working arrangements can be
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future. Fueled by curiosity and a deep sense of duty, they contribute invaluable insights to research and teaching, enriching our society. Are you inspired and driven by the desire to make a meaningful
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of Civil and Environmental Engineering / Chaney Lab: Perform the core of the proposed research activities including processing the remotely sensed LST to compute the spatial statistics, run the HydroBlocks
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conducting field work. Experience in teaching and supervision of undergraduate and MSc students. Experience with remote sensing, land-use and/or global climate data, including observed and modeled