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project will develop a physics-informed digital twin for offshore wind foundations, combining ultrasonic guided wave monitoring, high-fidelity finite element simulations, Bayesian inference, and machine
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conferences in areas of machine learning, computer vision, and Large Language Models and high-impact specialist peer reviewed academic journals. • Ability to conduct interdisciplinary research activities
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. State-of-the-art digital models and AI tools that incorporate machine learning could enable predictions of the dry fibre forming that are subsequently used as input into the RTM process model. The EngD
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at FHEQ level 7 (Master’s level) across AI foundations and machine learning to learners from varied academic and professional backgrounds. Ability to develop and deliver high quality and innovative teaching
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Provide human experts with a reliable second opinion This project integrates image processing, data analytics, machine learning, and computational modelling, with applications in aerospace, mechanical
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The postdoctoral researcher will lead the development of computational methods for aligning cortical organisation across species using transcriptomic and anatomical data combined with modern machine
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the Imperial Small Vessel Disease group. You will learn and perform physiological assessments including transcranial Doppler and cardiovascular physiology, as well as MRI imaging studies including respiratory
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testing. Experience of working with genomic data at a population scale, including the tools and technologies to manage sophisticated analyses. Experience of statistical and/or machine learning methods
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development, machine learning, public interest technologies, digital literacy, sensors, networks, or other EPSRC-relevant technologies. One week you might prototype a low-cost data collection tool; the next you
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of the FE STEM curriculum Oversee the cross-college delivery of GCSE Maths and English Drive improvements in teaching, learning and assessment Monitor performance metrics and lead quality improvement