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creative research environment with many opportunities. The group conducts cutting-edge research using large multimodal health data, deep learning, and translational science. The section has a collaborative
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us to explore the relation between the degree and type of processing, and the foods that result from their use. The results will be used for data machine learning, in collaboration with other partners
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to enhance imaging quality and speed Creating efficient data acquisition and processing workflows for large datasets of skin nanotexture images Optimizing hardware-software integration for robust performance
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large research consortium led from University of Copenhagen with partner universities in Norway, Austria, Czechia, Slovenia and the UK. The post.doc will work closely together with the Work Package on
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within our portfolio of hypothesis-generating screening studies, a methodological portfolio where we identify signals of interest from real-world register data to guide the conduct of tailored studies. We
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image quality in time-resolved micro and nano CT data. Develop and apply numerical implementations in simulation studies as well as to large experimental micro and nano CT data. Explore multi-modality
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Postdoc in Psychiatric Epidemiology: Linking Register and Trial Data to Study Postpartum Depressi...
digital treatment of maternal postpartum depression also benefits child outcomes. Initially, the postdoc will focus on conducting register-based studies using national health and administrative data. As the
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. Rapeseed is a protein-rich crop used for industrial oil production. It is cultivated on a large scale in Europe and may be utilized in new food types locally across the globe. In SEEDFOOD we will create