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excellence of NTU and attracting interest of more industrial collaborators. Key Responsibilities: Develop a new and robust numerical model with lattice Boltzmann method to simulate flow and heat transfer with
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transport à longue distance des microplastiques dans la troposphère libre et proposé des premiers bilans globaux du cycle des plastiques. Des simulations avec le modèle atmosphérique GEOS-Chem ont également
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-order modelling and high-fidelity simulations of turbulent reacting flows. You will have the opportunity of using cutting-edge facilities such as Imperial College HPC facilities. You will have access
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The Postdoctoral Researcher will join a new interdisciplinary project developing an AI-augmented decision science platform to understand and model high-stakes human judgments. This position will be jointly mentored
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, graph neural networks, physics-informed ML) to approximate PF results Train models using simulation results generated from conventional power flow solvers Evaluate AI-based approximators in terms
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methods for multiphase flow models Integrate experimental, pilot-scale, or high-fidelity simulation data into model calibration and validation workflows Design and run numerical simulations of multiphase
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and generative models, scale training on real data, and validate in simulation and with industry partners to advance safe, reliable automation. About us The Department of Computer Science and
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partners across the aerospace industry. BladeUp aims to transform wind turbine blade design and manufacturing using advanced modelling, machine learning and high-performance simulation, while Gradient Shells
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); j.wen@surrey.ac.uk . Information about research activities at FMEG can be found here: https://www.surrey.ac.uk/fire-and-explosion-modelling-group
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individual will implement, simulate and analyze models of epileptic source localization from EEG signals. Collaborate with clinicians to obtain and analyze imaging, EEG, and outcome data. Prepare results