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and spatial distribution” in the Research Unit Coastal Seas and Society until the 30.11.2027 and a percentage of 100% (40h/week), subject to the funding of the project. Remuneration is paid in
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identifying climate-resilient restoration sites in the Baltic Sea. The project integrates regional climate modeling, AI-driven simulations, and biogeochemical modeling to predict seagrass distribution under
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-learning algorithms Versatile data-science knowledge, including image and DNA sequences processing Programming skills in Python or other modern programming languages supporting AI and bioinformatics
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for new quantum computing algorithms. It will rely on statistical structure learning represented by knowledge graphs and efficient low-rank tensor compressions. We are looking for: A completed scientific
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near-real-time forecast system for the Baltic Sea Generate high-resolution daily surface salinity maps for the Baltic Sea and validate them with available observational datasets Develop algorithms and
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modeling, AI-driven simulations, optical remote sensing and biogeochemical modeling to predict seagrass distribution under various climate and nutrient scenarios. SEAGUARD aims to provide science-based