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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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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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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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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
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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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fields). Strong quantitative skills and demonstrated expertise in predictive modeling and advanced computational methods (e.g., Multilevel Vector Autoregressive Models, Dynamic Structural Equation
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). Applying advanced statistical and machine learning methods (e.g., predictive modelling, clustering, multivariate integration) to large-scale time series and sensor datasets. Contributing to the development
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is searching for a Control Engineer for developing health-aware model predictive control (MPC) for fuel cell hybrid electric vehicles (FCHEVs). Fuel Cell HEVs provide a long-term solution to
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experimental and computational datasets. The overarching objective of this work is to establish predictive, patient-specific models capable of forecasting clinical outcomes in breast reconstruction, thereby