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or mentally struggling. We work respectfully with people from different backgrounds, experiences and nationalities. To collaborate more efficiently and ensure reproducibility, we implement the principles
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qualifications: Strong experience in programming using Python, R, or other languages Research experience in remote sensing of cover crop, crop type classification, and crop biomass Insight into global
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., CNNs, UNets, Transformers) Demonstrated experience working with satellite data, particularly SAR and multi-spectral imagery Strong programming skills in Python and hands-on experience with deep learning
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wildfires and their impacts on both the stratosphere and climate combining different model systems. The position is to be filled by 1 May 2026 or as soon as possible thereafter. Expected start date and
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be working primarily with scientific machine learning methods, including symbolic regression and neural networks. You will apply the algorithms to the discovery of new models in different fields
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on retrospective Danish data. The research will include testing different levels of model scaling in terms of data amount and diversity, and training will take place both on a local GPU cluster and on the Gefion
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: Extensive experience in programming using Python, R, or other languages Research experience in remote sensing of cover crop, crop type classification, and crop aboveground biomass quantification Insight