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the noise associated with near-term quantum devices. This in turn offers an exciting new dataset from which it will be possible to use machine learning to train a more accurate functional for use in density
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reduce risk in early-years nursery settings through both proactive prevention and reactive response. About you Degree (1st or 2:1) or equivalent in AI, Computer Vision, Machine Learning, Data Science (ML
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Apply and key information This project is funded by: Department for the Economy (DfE) Summary CNC machining delivers high precision but is costly, rigid, and limited in adaptability. Robotic
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PhD at the Forefront of Computational Solid Mechanics and Machine Learning School of Mechanical, Aerospace and Civil Engineering PhD Research Project Self Funded Dr J L Curiel Sosa Application
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application of innovative Machine Learning (ML) frameworks to understand and predict the global hydrological cycle. The role will require bridging the gap between process-based physical modeling and scalable
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). The project investigates how machine learning (ML) can be used to enhance the modelling of boundary layers in industrial CFD simulations, where complex geometries and computational constraints limit near-wall
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Machine Learning Quantum Phase Transitions via Topology- and Symmetry-aware AI School of Mathematical and Physical Sciences PhD Research Project Self Funded Dr Marco Fazzi Application Deadline
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specialised expertise in the Machine Learning for Engineering sub-theme. Candidates from all areas in machine learning are encouraged to apply, with a special focus on the areas of (i) information theory and
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the design, development, deployment and evaluation of NeoShield’s applied machine-learning systems, the machine-learning-driven Clinical Decision Support Algorithm for neonatal sepsis and the real-time ward
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Machine Learning Methods for Enhancing Autonomy of Unmanned Aerial Vehicles in Wildfire Detection and Localisation School of Electrical and Electronic Engineering PhD Research Project Self Funded