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As the German National Library of Science and Technology our future-oriented services ensure the infrastructural requirements for a high-quality supply of information and literature for research in
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for the following as soon as possible one student assistant (f/m/d) for 10 hours per week You will contribute to the survey methodological research of the data, including the preparation, testing, analysis and
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and other stakeholders - knowledge-driven and application-inspired. FAIRagro is a consortium within the National Research Data Infrastructure (NFDI) in Germany. Its goals and activities focus
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protection information on the processing of personal data as part of the application and selection process, please refer to the privacy policy on our homepage at https://www.senckenberg.de/en/imprint/ Please
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Student or Scientific Assistant for Remote Sensing Data Processing and Cloud-based Workflows (f/m/d)
or Scientific Assistant for Remote Sensing Data Processing and Cloud-based Workflows (f/m/d) Your tasks: Support in processing satellite and UAV remote sensing data on cloud platforms Adaptation and optimization
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strategic extension of ZMT entitled ‘Modelling Socio-Economic Dimensions Across Tropical Coastal Ecosystems and the Earth system – TropEcS ’ aims to link the existing research capacities of ZMT in the fields
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strategic extension of ZMT entitled ‘Modeling Socio-Economic Dimensions in Tropical Coastal Ecosystems and the Earth system – TropEcS ’ aims to link the existing research capacities of ZMT in the fields
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modelling component that links physical and ecological processes and further enhances ZMT’s interdisciplinary research on ecosystem and socio-economic dynamics. Therefore (subject to release of funds), we
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particular type of laser diode used in data communication and sensing applications, e.g. face recognition, LIDAR and altitude control in satellites. VCSELs show a characteristic white-light reflectance
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based on machine learning. Reference number 08/26 Your tasks 1. Assessment and analysis of GaN technology characterization data Identification of outliers during testing, with and without machine learning