104 model-driven-development "Integreat Norwegian Centre for Knowledge driven Machine Learning" Postdoctoral positions in Denmark
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). GreenFjords takes an interdisciplinary approach to study the long-term environmental and climatic development of five fjord systems in northeast Greenland: Dove Bay, Ardencaple Fjord, Young Sound, Kong Oscar
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textiles. The projects are carried out in close collaboration with industrial and societal partners and aim to develop, test, and implement innovative circular concepts and business models that reduce
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Postdoc positions in Organic Chemistry: developing the next generation super materials for sustainable industrial polymer products Department of Chemistry Organic Chemistry Section Faculty
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extending to 2100 and, where appropriate, 2300; develop and/or integrate hierarchical species distribution models and/or dynamic vegetation modelling approaches, using contemporary and historical biodiversity
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thereafter. Explaining complex AI models is a key challenge for ethically responsible AI. Explainable AI (XAI) research aims to provide relevant information to assist developers and users in analyzing AI
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Are you interested in advancing our understanding of fracture and damage tolerance in fibre reinforced polymer composites, and in contributing to the development of new modelling approaches
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Biological Section and the Centre for Gelatinous Plankton Ecology & Evolution, lead by Senior Scientist Dr. Cornelia Jaspers. The postdoc is funded via the Danish Research Council and the DFF2 project - Marine
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to pharmacological intervention. We will combine studies in GPR6 knockout mice with pharmacological approaches in rodent models, including Flinders Sensitive Line (FSL) rats, a model of depression. By linking
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postdoctoral researcher to join an interdisciplinary team developing deep learning models for antimicrobial resistance (AMR) detection directly from MALDI-TOF mass spectrometry data. The project is funded
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. The tasks include battery cell characterization and modelling based on laboratory tests, and development of algorithms for estimating the charge level, health, and power capability which includes robustness