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datasets, UAV-derived information on NBS, and environmental data to quantify ecosystem services across Danish agricultural landscapes. The postdoc will work within an interdisciplinary team of applied and
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and personalised medicine. The Department of Biomedicine provides research-based teaching of the highest quality and is responsible for a large part of the medical degree programme. Academic staff
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, neuroscience and personalised medicine. The Department of Biomedicine provides research-based teaching of the highest quality and is responsible for a large part of the medical degree programme. Academic staff
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include psychiatric disorders as well as clinical and social outcomes, but specific tasks may depend on applicants. The positions will generally involve various data analyses using Danish register data and
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” funded by Independent Research Fund Denmark and led by Associate Professor Christoffer Basse Eriksen. The project aims to carry out the first large-scale study of the making of the Flora Danica (1761–1883
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research in deep learning models for multi-sensor satellite data (e.g. SAR, SMAP) within a large international research project on AI-driven solutions for groundwater management. Expected start date and
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hold a PhD in oceanography, marine ecology, computer sciences, data sciences or similar. We expect that you have: Expert knowledge on network modelling, especially aimed at ecological applications Strong
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, conducting interviews, analyzing interview transcripts, and writing academic articles based on the data. YOPOW seeks to deliver cross-national evidence across the three work packages, with work package II
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, neuroscience and personalised medicine. The Department of Biomedicine provides research-based teaching of the highest quality and is responsible for a large part of the medical degree programme. Academic staff
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., camera traps, thermal imaging, acoustic sensors) Practical skills in programming and analysis of large datasets Publication record in relevant areas Ability to communicate effectively in English, both