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storage potential and future carbon removal and carbon farming policy scenarios. It integrates process-based knowledge with machine learning and especially aims to spatially quantify uncertainties. You will
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storage potential and future carbon removal and carbon farming policy scenarios. It integrates process-based knowledge with machine learning and especially aims to spatially quantify uncertainties. You will
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. You have a background in machine learning for spatial data (e.g., random forest, neural networks) or are open acquiring these skills. You have experience with handling large geospatial datasets and
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to predict precipitation fields over the Greenland Ice Sheet and the Himalaya in one combined project. For the Greenland Ice Sheet, the focus is on the spatial precipitation distribution on monthly and yearly
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. You have a background in machine learning for spatial data (e.g., random forest, neural networks) or are open acquiring these skills. You have experience with handling large geospatial datasets and
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are as follows: Estimate the onshore technical and economic potential for CCUS in rural areas in Germany, the Netherlands and Norway. Gather high resolution spatial explicit data on (potential) CO2 sinks