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Field
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and student supervision? Have you recently earned a PhD in Remote Sensing, or are you about to finish your PhD, and feel inspired to share your expertise with the next generation while advancing your
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data and deep learning methods to assess canopy cover, quality, carbon stocks, and ecosystem services. Mandatory requirements: PhD in areas related to forest resources, remote sensing, data science, or
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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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and analyses based on various input data sets from eDNA, remote sensing and biodiversity observations? Department of Biology advertises a postdoc position focused on data integration and visualisation
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circumstances, the doctoral degree can have been completed earlier. Additional requirements: PhD in physical geography, remote sensing, geoinformatics, forest ecology, environmental science, or a closely related
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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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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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available at CC, with a primary focus on Artificial Intelligence within the field of Agriculture/ Remote sensing (not limited). The successful candidate will join a dynamic, multidisciplinary team and have
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autonomous workflows. with a primary focus on Artificial Intelligence within the field of Agriculture/ Remote sensing (not limited). The successful candidate will join a dynamic, multidisciplinary team and
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Max Planck Institute of Animal Behavior, Radolfzell / Konstanz | Konstanz, Baden W rttemberg | Germany | 2 days ago
libitum’ data. Experience in collecting and/or analyzing survey data (CT, PAM, Telemetry) Experience in remote sensing Organization skills, reliability, and a thorough work style with attention to detail