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on combining innovative technologies such as remote monitoring, large language models, machine learning, blockchain, and eco-accounting to enhance the efficiency, security, and sustainability of e-bike charging
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Deliver a highly customisable multiphysics CFD framework for laser drilling and integrate it into accelerated industrial workflows. You will: Extend XCALibre.jl with new (traditional and/or AI-enhanced
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tailored trajectory guidance. Enhancing Robot Autonomy: Enabling robots to improve their own performance by learning from operator data, ultimately enhancing their ability to assist in complex tasks. Key
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highly customisable multiphysics CFD framework for laser drilling and integrate it into accelerated industrial workflows. You will: Extend XCALibre.jl with new (traditional and/or AI-enhanced) models
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Are you passionate about artificial intelligence, data analytics, and cutting-edge engineering applications? Join our interdisciplinary research team and contribute to the future of Non-Destructive
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. The successful candidate will receive an annual tax-free stipend set at the UKRI rate (£20,780 for 2025/26) and tuition fees will be paid. We expect the stipend to increase each year. We recommend that you apply
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4 Dec 2025 Job Information Organisation/Company IFP Energies nouvelles (IFPEN) Research Field Physics » Applied physics Engineering » Water resources engineering Environmental science » Earth
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models to enhance learning through AI technology. A part of this work is also to consider opportunities for innovation related to start-up companies. The approach followed encapsulates Design-Based
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harness advanced techniques such as machine learning, optimization algorithms, and sensitivity analysis to automate and enhance the mode selection process. The result will be a scalable methodology that
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their applications. Using machine learning and related tools to enhance quantum memory advantages in stochastic simulation. Using advanced tensor network techniques to enhance the modelling of complex, memoryful open