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-climatic Extremes (GENAI-X)«, funded by the Carl-Zeiss-Stiftung, addresses a fundamental AI challenge: achieving robust model generalizability in non-stationary environmental systems. Focusing on hydro
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. Multiscale simulations of the downstream expansion behaviour of the engine exhaust plume for different atmospheric layers. Definition of suitable interfaces to process data for the climate models. Expected
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climate because they interact with radiation from the sun and from the earth. However, the aerosol-cirrus interaction in the UTLS is not well understood because of lacking sufficient in situ data. In
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opportunity to be part of the project “Bavarian Artificial Intelligence for Insect Monitoring” (https://go.ur.de/baimo ), which investigates the effects of climate change on insect populations as part of
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of the downstream expansion behaviour of the engine exhaust plume for different atmospheric layers. Definition of suitable interfaces to process data for the climate models. Expected Results: Ability to assess
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Additional information on beginning, duration and mode of study The starting date of the PhD project is flexible. The initial funding period is usually three years. Find out more at https://www.bgc-jena.mpg.de
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremerhaven, Bremen | Germany | 29 days ago
response to anthropogenic climate change. Understanding its state during past warm periods is pivotal to aid our ability to project future changes. Arctic Ocean sediments provide such a window into the
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vehicle. Multiscale simulations of the downstream expansion behaviour of the residuals for different atmospheric layers. Definition of suitable interfaces to process data for the climate models. Expected
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about their climate impact. Tasks: Research Objectives: Definition of a suitable interface region based on the results from other IRP. Numerical analysis of the emission propagation in the near field
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& Development), focuses on assessing the CO₂ storage potential of seagrass meadows and identifying climate-resilient restoration sites in the Baltic Sea. The project integrates regional climate modeling, AI