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collaboration with an interdisciplinary team including biologists, pedologists and other experts. You will work with various types of spatial data collected from multiple sources and at different scales. We
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functionalities (GUI and web-service) Participate in field work organization, sampling plan establishment and in-situ data acquisition Your Profile PhD in environmental sciences or computer science, with a proven
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: PhD in Veterinary Epidemiology or a related field, or demonstrated experience with epidemiology Strong quantitative data analysis skills Applied understanding of epidemiological principles Demonstrated
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leverage graph structures to represent, integrate and analyze multi-modal data, employing advanced machine learning techniques to address complex questions in biology. The team is focusing on different
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machine learning. The research at DTU Bioinformatics is focused on bioinformatics and computational analyses of large amounts of data generated within biological, biomedical and biotechnological and life
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analyses of large amounts of data generated within biological, biomedical and biotechnological and life sciences area. We strive to gain new knowledge and drive innovation in human, animal, plant and food
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targets, by leveraging high-dimensional big data (e.g. electronic health records, multi-omics and phenotypic) from large prospective biobanks including China Kadoorie Biobank (CKB) and UK Biobank (UKB), and