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an open 2-year postdoc position in relation EUROfusion; specifically, on remote maintenance of fusion power plants. The project is on modelling and controller design for the transporter robot for extracting
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Denmark (SDU). The position is in an exciting 6-year project supported by the Challenge Programme of the Novo Nordisk Foundation: “Mathematical Modelling for Microbial Community Induced Metabolic Diseases
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transcriptomics and bioimaging to study human liver biopsies and advanced, preclinical models. A combination of wet-lab and computational biology, close ties to the clinic, and a wonderful team of early career
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the kidney’s electrolyte and water reabsorption. The postdoc will be expected to explore the potential of modulating bile acid signaling in cell and mouse models and perform metabolomic and transcriptomic
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cell-specific transgenic strategies coupled with detailed physiological characterization of these models. This will be done using a variety of techniques including metabolic cage studies in mice, a range
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synergistically integrates innovative oceanographic, biogeochemical, ecophysiological, and model-based investigations. The main research objective is the exploration and quantification of non-photosynthetic sources
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project supported by the Challenge Programme of the Novo Nordisk Foundation: “Mathematical Modelling for Microbial Community Induced Metabolic Diseases”, led by Prof. Daniel Merkle. The expected starting
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of the extremely wealthy individual. The postdoc project enquires into these ethical obligations and should aim to sketch a model of the moral requirements of being extremely rich. We expect the postdoc project
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techniques. Experience with data-driven user modeling and AI-driven personalization (e.g., recommender systems, user profiling, or adaptive user interfaces) is highly desirable. Knowledge of or a passion for
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translated into English. The application documents must be written in English. Use of large language models or related AI tools in any capacity must be disclosed in accordance with best academic practices