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augmentation for soil and biomass carbon forecasts and scenario modelling across Europe; developing and benchmarking uncertainty quantification methods for space-time predictions and for spatial blocks
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background and interests. Candidate Profile We are looking for candidates who meet the following criteria: PhD in a related discipline. Expertise in one of the following areas: Single-cell and spatial
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with partners across Europe: data sharing, code exchange, joint publications and reporting. Your qualities You hold a PhD (or near completion) in Soil Science, Environmental Modelling, Biogeochemistry
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augmentation for soil and biomass carbon forecasts and scenario modelling across Europe; developing and benchmarking uncertainty quantification methods for space-time predictions and for spatial blocks
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Postdoc in modelling Greenland and Himalaya precipitation using machine learning Faculty: Faculty of Science Department: Department of Physics Hours per week: 36 to 40 Application deadline: 26
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with partners across Europe: data sharing, code exchange, joint publications and reporting. Your qualities You hold a PhD (or near completion) in Soil Science, Environmental Modelling, Biogeochemistry
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are not designed to produce reliable regional estimates of those phenomena. Therefore, small area estimation (SAE) methods are used. With technological advances, Big Data now offers valuable spatial
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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
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to build predictive models Collaborate closely with experimentalists and modelling experts Project Environment This position is part of a collaborative research project involving: Two PhD students at TU