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Field
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developing methods/tools that use multisource remotely sensed data. The research aims to improve our understanding of the integrated functioning of continental surfaces and their interaction with climate and
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in Europe; Analysis and integration of collected data and publicly available databases (e.g., FLUXNET, ICOS, remote sensing dataset); Co-supervise doctoral students and collaborate with other MPI and
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Your Job: You will join the Simulation and Data Lab `AI and ML for Remote Sensing,` which aims to enhance visibility in interdisciplinary research between applications from remote sensing and large
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activity, and coastal protection benefits in the Caribbean. The postdoc will lead the development and application of a modeling framework to integrate remotely sensed datasets with coastal hydrodynamic
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Simulation and Data Lab `AI and ML for Remote Sensing,` which aims to enhance visibility in interdisciplinary research between applications from remote sensing and large-scale AI with high-performance and
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in the Arctic and Antarctica using remote sensing, laboratory measurements, and field data. The candidate will be based at OSU, but will have opportunities to work directly with co-investigators
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available from 01/04/2024 to 31/03/2025. The successful applicant will combine remotely sensed datasets with machine learning to map peat extents, habitats, habitat condition and change. The post will include
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on-site at the Lawrence, KS campus with the possibility of a hybrid (remote and on-site work) schedule as deemed by the supervisor. The position will require occasional overnight travel to field sites
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the possibility of extension,based on satisfactory performance. This position has the ability to regularly be performed at least partially remotely, with 4 days on campus and one day remote per week. Supervision
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institute with around 300 colleagues, where diversity, equal opportunities, and a healthy work-life balance guide all areas of work. Flexible work schedules tailored to your needs as well as remote work