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programmes of research, working with synthetic chemists to test our machine learning systems against challenging real world examples. The role holder will lead on a programme of computation and experimental
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symbiosis of cutting-edge AI combined with human support. About the role The Research Scientist in Machine Learning for Wearables will develop predictive deep learning models to assess maternal and partner
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symbiosis of cutting-edge AI combined with human support. About the role The Research Scientist in Machine Learning for Wearables will develop predictive deep learning models to assess maternal and partner
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About the role This project will develop new machine learning techniques to enable efficient production of bespoke products, such as medicines in a high-volume, high-variation manufacturing setting
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About the role This project will develop new machine learning techniques to enable efficient production of bespoke products, such as medicines in a high-volume, high-variation manufacturing setting
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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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knowledge of power system security and machine learning being crucial. The Associate will primarily work alongside National Grid engineers to integrate the machine learning backend of the intrusion detection
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innovative Learning Designer (Inclusive Curriculum) for a fixed term post until 31st July 2029 to support us to transform learning champion inclusion and accessibility and ensure we are delivering excellence
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EngD: Physics-based AI for Intelligent Machining: Learning, Optimisation, and Uncertainty in Next-Generation CAM Software (sponsored by DigitalCNC) EPSRC Centre for Doctoral Training in Machining
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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