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, predictive modelling, and autonomous maintenance solutions. You thrive on scientific discovery, enjoy tackling complex multi-physics problems, and have the drive to explore innovative concepts
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is to move beyond traditional “check-after” approaches and instead predict and prevent errors while the radiotherapy treatment is being delivered. The candidate will build upon this existing prototype
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Kogias as part of his ERC Starting project titled CloudNG (https://cordis.europa.eu/project/id/101220079 ). The post will be based in the Department of Computing at Imperial College London at the South
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related topic and need to have expertise in working with data from the National Drug Treatment Monitoring System (NDTMS), working with government and expertise in quantitative prediction modelling
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better quality of life for patients and caregivers, and lower healthcare costs. The target is to define new intelligent computational models by reshaping risk prediction, diagnosis, and management of a
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analytics, predictive modeling, and related fields. We welcome applicants committed to addressing complex challenges in sport analytics, tourism analytics, human performance, and related fields. Candidates
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monitoring. • Develop numerical models to simulate the dynamic behavior of mooring and anchoring systems under different environmental conditions. • Analyze and optimize structural performance and predictive
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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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on creating and optimizing state-of-charge (SOC) and state-of-health (SOH) prediction models to ensure the safety, efficiency, and longevity of lithium iron phosphate (LFP) batteries. Key Responsibilities
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well as experience with simulation model calibration, validation, and prediction. While efforts will be collaborative, the person in the role is expected to work independently and publish results through scientific