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models ranging from baseline approaches to graph neural networks. You will also oversee the open release of project datasets, models, code and documentation. The successful candidate will join Oxford's
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and sustainability; Investigate and apply artificial intelligence and machine learning techniques, including large language models (LLMs), across CENSE’s scientific body in its five thematic areas
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animal movement analyses. Geospatial analysis, GIS, and remote sensing. Statistical, ecological, and machine-learning modeling using modern analytical software (e.g., R or Python). Google Earth Engine and
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or professional experience in the field of soil indicators development, soil health assessments, soil monitoring and modelling. The experience should be proven and cover at least 1 year of activity. • Extensive
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at the time of appointment; Research experience in agricultural remote sensing, crop and pasture modeling, or agricultural environment monitoring and prediction; Knowledge of remote sensing, geospatial