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Field
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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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postdoctoral and PhD researchers on the team*Interest in developing and applying Large Language Models (LLM) and spatial Machine Learning (ML) modelsSalary and full employee benefits are offered in accordance
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part of our team, you will leverage state-of-the-art single-cell, spatial and organoid technologies in a collaborative and interdisciplinary environment. Research focus We welcome candidates with a
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Postdoc: Hybrid Geospatial Modelling and Scenario Development of Carbon Faculty: Faculty of Geosciences Department: Department of Physical Geography Hours per week: 32 to 40 Application deadline
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of techniques for countering information maneuvers, differences in online harms and influence campaigns across countries, geo-spatial differences in online harms. Successful applicants will need experience in
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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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Department: Computer Science Vacancy ID: 036943 Closing Date: 31-Aug-2025 We are seeking an experienced Earth Observation and Modelling scientist who has knowledge of, and expertise in analysing
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We are seeking an experienced Earth Observation and Modelling scientist who has knowledge of, and expertise in analysing Earth Observation data including Satellite Remote Sensing together with Soil
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practices ● Fluency in programming languages such as R and Python. ● Demonstrated ability to make reproducible code for cleaning, integrating, and modeling spatial/temporal data from multiple sources, spatial
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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