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science, computer vision, medical/image analysis is essential. Experience of research (or interest in) in one or more of the following: deep learning; big data management; computational pathology; medical imaging
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significant advancements with the integration of Artificial Intelligence (AI) and Machine Learning (ML) techniques. This PhD research aims to explore the development and application of Process Induced Neural
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subsystems • High performance tunable and reconfigurable oscillators and frequency synthesisers • Application of AI / Machine Learning to physical layer circuitry, signals and waveforms Researchers can expect
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). Modelling tools used will vary according to application but are likely to including process simulation using Population Balance Modelling, DEM simulations and Machine Learning Approaches. Main duties and
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Machine Learning Methods for Autonomous Robot Navigation, Localisation and Pipe Inspection School of Electrical and Electronic Engineering PhD Research Project Self Funded Prof Lyudmila Mihaylova
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capable of predicting boiling and CHF in PWR-relevant conditions. Combining improved physical modelling with the potential of machine learning and data assimilation techniques, you will specifically target
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Artificial intelligence and machine learning methods for model discovery in the social sciences School of Electrical and Electronic Engineering PhD Research Project Self Funded Prof Robin Purshouse