200 machine-learning "https:" "https:" "https:" "https:" "EMBL EBI European Bioinformatics Institute" Postdoctoral positions in Denmark
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be to: Conduct multidisciplinary research (as explained above) Teach (and design) BSc and MSc courses, Supervise BSc and MSc student projects, Supervise PhD students as a co-supervisor for PhD students
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written and spoken Willingness to engage in interdisciplinary collaboration and fieldwork Advantageous: Knowledge of bat ecology and species identification Experience with machine learning or automated
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quality and climate. Our goal is to understand how these gases are produced and removed in peatlands and to bring this knowledge into climate models. Project links - https://villumfonden.dk/en/projekt
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The Daasbjerg research group at the Department of Chemistry, Aarhus University, is seeking a candidate for a 31-month postdoctoral position. This position focuses on AI/machine learning to develop a
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The Daasbjerg research group at the Department of Chemistry, Aarhus University, is seeking a candidate for a 31-month postdoctoral position. This position focuses on AI/machine learning to develop a
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employ cutting-edge single-cell and spatial omics technologies with bioinformatics and machine learning to decipher principles of gene regulation underlying cell identity and its disruption in human
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of green energy technologies (https://www.sdu.dk/da/forskning/cape), and we are looking for a highly motivated researcher with a PhD to join our research team at the University of Southern Denmark (SDU
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or soon thereafter, and the position offers a full-time (37 hours) contract, in 10 months. The candidate will conduct cutting-edge research in Human-Computer Interaction, with a focus on novel interactive
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biology, epidimological data and AI-driven systems modeling. The successful candidate will develop and apply computational and machine learning approaches to decode the molecular and epigenetic mechanisms
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include: Supporting the delivery of the 3D-CIRCULAR master and doctorate programmes, including coordination of hybrid (online/in-person) teaching and supervision activities. Updating and refining learning