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-layer and cloud processes in the air-mass transformations that follow moist intrusion events into the Arctic. Using large-eddy simulation models, you will set up and run case studies of observed air-mass
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Max Planck Institute for Plasma Physics (Garching), Garching | Garching an der Alz, Bayern | Germany | about 4 hours ago
with the IPP-NBI team. Strong collaboration with the NBTF team and related experiments is requested. Your tasks Responsible for operation of the beam diagnostics at the test facilities Analyze
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Association. ZPID is undergoing a strategic extension process aimed at becoming a one-stop, full-service provider supporting the entire spectrum of needs expressed by researchers and psychology professionals
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analysis, simulation, chemometrics, control engineering, artificial intelligence, soft sensors, and process sensors. We are always looking for new technologies and new methods to monitor and optimize
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mass transfer, and process engineering Extensive experience in modeling and simulation and ideally knowledge of CFD software (e.g., Ansys Fluent, OpenFOAM, COMSOL) Very good programming skills
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intelligence methods for data analysis, including image data processing present results through reports and presentations to scientific and clinical audiences perform heterogeneous data analysis in the context
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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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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
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Postdoc (f/m/d) Research Data Management and Data Visualization / Completed university studies (P...
-spatial data, and simulated model data # Design and extend data handling and data management solutions; based on this, design and implement procedures and workflows for the project # Adapt workflow systems
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aims to shed light on AMOC variability and change during the last two millennia by combining climate model simulations with proxy data, using particle filter data assimilation, and to link