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lack the tools to predict the impact of industrial processes on natural biological diversity, thereby limiting our ability to conserve critical resources and the services they provide. One of the main
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to experimentally test predicted models would be appreciated. Website for additional job details https://emploi.cnrs.fr/Offres/CDD/UPR2357-PATACH-008/Default.aspx Work Location(s) Number of offers available1Company
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quantitative predictions testable against empirical data from diverse ecological contexts. We use methods from theoretical evolutionary biology, including optimal control theory, life history modelling, adaptive
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Post-Doctoral Associate in Sand Hazards and Opportunities for Resilience, Energy, and Sustainability
research on the integration of Digital Twins with AI/ML technologies for infrastructure lifecycle management. Develop and validate computational models for monitoring and predicting infrastructure
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to combine high-throughput metabolomics with 3D cell culture models Perform large chemical and genetic studies in cancer cell lines derived spheroids Develop predictive model of drug response by comparing 2D
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and observation models to reflect real-time changes in environmental conditions, enabling more accurate predictions of adaptation impacts and thereby supporting a better-informed, resilient decision
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Have you always wondered how neural models process information? Are you
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field. This approach is related to data assimilation, allowing for better prediction, control, and optimisation of turbulent systems in engineering, energy, and environmental applications
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Monitoring Duties & Responsibilities: Build early warning and clinical deterioration prediction models Develop continuous clinical risk trajectory modeling frameworks Model time-series data such as vitals
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a passionate community collectively aiming to bring novel technologies and science to cutting-edge numerical weather prediction. ECMWF has been the first operational weather centre globally to