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affect resource availability and infrastructure. This thesis will explore how disruptive scenarios impact renewable energy potentials across Germany, by combining Python-based GIS workflows with energy
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programming skills in Python and R Experience in software development, particularly in dashboard or web application creation Familiarity with geospatial analysis, GIS tools, or related technologies is a plus
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Schulz E-Mail: gi-personal@ime.fraunhofer.de Phone: +49 641 972-19203 Fraunhofer Institute for Molecular Biology and Applied Ecology IME, Bioresources institute branch www.ime.fraunhofer.de Requisition
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of GIS software as well as word processing and spreadsheet programs Knowledge of programming languages such as R or Python desirable Experience in organizing workshops is desirable Very good written and
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qualification (doctorate) Requirements: Completed scientific university degree in geography, (geo)informatics, landscape ecology or comparable disciplines Profound knowledge of GIS software, programming languages
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) Experience in coordinating and managing inter- and transdisciplinary research projects Strong communication and collaboration skills Experience in academic work and scientific publishing Knowledge of GIS and
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geology, and geodesy Good field expertise in active tectonics and paleoseismology; knowledge of Balkans/Aegean geology is a plus Experience with structural/kinematic analysis and GIS Strong communication
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Temporal Dynamics”. We intend to strengthen our existing expertise by an expert in benthic ecology and taxonomy of North Sea infauna and epifauna as well as statistical benthic long-term data analysis, GIS
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Oldenburg Oldenburg, Niedersachsen | Germany | about 2 months ago
policy Experience with remote sensing and spatial-modelling tools (e.g., GIS) Supervisory or teaching experience Experience in setting up and managing collaborative relational database Further information
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experience with spatial data analysis using GIS tools or spatial libraries and familiarity with common land-use datasets would be advantageous familiarity with environmental or agricultural economics research