382 machine-learning-"https:" "https:" "https:" "https:" "https:" "University of St" "St" PhD positions in United Kingdom
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an appropriate discipline. Ideal candidate will have some prior knowledge in deep learning and computer graphics. Subject Area Medical imaging, biomedical engineering, computer science & IT
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integrating machine learning, computational modelling, and experimental validation. The successful candidate will receive training in both computational and experimental biology within a highly collaborative
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into the sample of interest. Recently we have been using AI and machine learning to predict the distortion present and significantly speed up this correction process. This PhD project will take the latest in AI
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feedback using machine learning and control engineering methods. The project will be hosted at the Bristol Robotics Laboratory (BRL), the UK’s largest academic centre for robotics research, with access
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on basic laparoscopic surgery tasks, using data collected under varying network conditions and applying machine learning and time-series modelling to predict delay. The models will be integrated into a real
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. Strategies will centre on improved formulations of the mixed-integer constraints, as well as the use of machine learning to accelerate conventional solution algorithms (e.g. branch and bound). The second goal
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applications require precision machining to achieve their final geometries. If machining conditions are not kept within specification, then damage to the material can occur, which can be detrimental to fatigue
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experts at University Hospitals Coventry & Warwickshire/NHS Trust. The research will involve emulating laparoscopic surgical tasks using a robotic platform under varying network conditions. Machine learning
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: This 4 year fully funded studentship is open to applicants with a first-class or upper second-class degree (or equivalent) in Electrical Engineering, Machine Learning, Physics, Data Analytics or other
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this challenge head on by combining quantum-mechanical calculations with state-of-the-art machine learning (ML) methodologies to explore and optimise the compositional space of complex high-entropy metal oxides