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how genetic and environmental factors interactions shape mucosal immunity and metabolism. Our approach includes state-of-the-art multi-omics, novel organoid culture, genetically engineered murine models
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imaging specialist – experience in quantitative image analysis, scattering modeling, signal processing, machine learning, or neural-network-based data interpretation. The project is closely connected
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larger Vici project funded by the Dutch Research Council. FireSky is an interdisciplinary project combining field, remote sensing and modeling approaches to study feedbacks between climate warming
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in molecular biology, cellular biology, AI-based bioinformatics, and mouse models required, which includes single-cell RNA sequencing and data analysis, hydrodynamic injection, hepatocyte isolation
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The Monroe group at the Oxford University Department of Engineering Science seeks a full-time Postdoctoral Research Associate. This post is funded by the Faraday Institution Multiscale Modelling
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biochemical datasets. A major focus will be on introducing new AI models to chart the chemical “dark matter” of the mammalian metabolome; examples of such models include large supervised or self-supervised AI
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, and can analogous mechanisms be engineered into multi-agent AI systems? You would answer this question by building and testing computational models, developing multi-agent simulations where agents
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Council (ARC) to Professors Michael Keane and Alan Woodland. The grant supports research aimed at building more sophisticated labour supply models into macroeconomic models that are used for optimal tax
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developing next-generation AI methods for healthy climate adaptation. The position will focus on building and evaluating foundation models for large-scale spatiotemporal health and environmental data. Our team
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
modeling of large-scale dynamics in networks. This role involves creating large scale models of dynamic phenomena in electrical power networks and quantifying the risk of rare events to mitigate