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. You have a background in machine learning for spatial data (e.g., random forest, neural networks) or are open acquiring these skills. You have experience with handling large geospatial datasets and
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. You have a background in machine learning for spatial data (e.g., random forest, neural networks) or are open acquiring these skills. You have experience with handling large geospatial datasets and
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position of 1.0 FTE for 30 months or 0.8 FTE for 37 months; access to computational resources (HPC), GIS/data infrastructure, and datasets via collaborative networks; a supportive, interdisciplinary research
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pathology facilities, expertise in animal disease, and a strong network of national and international partners, we conduct comprehensive necropsies to identify mortality patterns and environmental threats
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position of 1.0 FTE for 30 months or 0.8 FTE for 37 months; access to computational resources (HPC), GIS/data infrastructure, and datasets via collaborative networks; a supportive, interdisciplinary research
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. These technologies are highly novel and one-of-a-kind, and the project is expected to result in several highly impactful publications. You will coordinate your work within an (inter)national network of collaborators