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quantitative genetics or animal breeding Has published high-quality research in peer-reviewed journals Experience with scripting languages (e.g., R, Python, SAS) and/or genetic software (e.g., DMU, ASReml) Can
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An ability to take initiative, develop, and manage research activities Proficient quantitative skills with data analysis and programming e.g. in R and python Documented experience in scientific writing and
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programming language (e.g., R, Python) Who we are At the Department of Agroecology, our main goal is to contribute to sustainable solutions to some of the world’s biggest problems within the areas of soil
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, or a related field Strong experience in spatial and/or landscape modelling Proficiency in R and/or Python Experience with GIS and remote sensing Ability to work with large and heterogeneous datasets
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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