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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 14 days ago
models and remote options create a supportive environment for balancing work and family life. For us, contributing to a healthier society in such an inspiring workplace is truly meaningful.“ Get to know us
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-driven simulations, optical remote sensing and biogeochemical modeling to predict seagrass distribution under various climate and nutrient scenarios. SEAGUARD aims to provide science-based recommendations
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to groundbreaking research and innovative solutions. Our flexible working models and remote options create a supportive environment for balancing work and family life. For us, contributing to a healthier society in
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the quality of open geodata through the combination of machine learning and multimodal remote sensing. Your responsibilities: Research related to the topics of the project and beyond Taking a leading
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W3 or W2 with tenure track to W3 professorship in General Geophysics / W2 professorship in Geographi
for applications. If you have any questions about the position and the procedure, please contact Prof. Dr. Falko Langenhorst at falko.langenhorst@uni-jena.de . W2 professorship in Geographical Remote Sensing/Earth
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Your Job: In this position, you will be an active member of our "Simulation and Data Lab for AI and Machine Learning in Remote Sensing", which aims to strengthen interdisciplinary research by
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–policy interface for municipal biodiversity conservation and climate adaptation with nature-based solutions Processing and evaluation of remote sensing data, including methods of computer vision
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., plants, cultivation trials, fields, and landscapes), and various data formats (e.g., farm and management data, time series, long-term field experiments, geodata such as remote sensing) very good knowledge
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, Geoscience, Remote Sensing, Hydrology, Data Science, Physics, or related fields • Experience in machine learning (ML), artificial intelligence (AI) or related fields • Software skills in ML languages such as
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, you will be an active member of our "Simulation and Data Lab for AI and Machine Learning in Remote Sensing", which aims to strengthen interdisciplinary research by bridging satellite remote sensing