381 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Simons Foundation" PhD positions in United Kingdom
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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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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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The Centre for National Training and Research Excellence in Understanding Behaviour (Centre-UB) in partnership with the King’s Centre for Military Health Research (KCMHR), King’s College London (KCL
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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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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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sciences, AI, machine learning or related fields. Strong background and track record in the development of geospatial foundation models from multi-modal Earth Observations is essential as well as strong
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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
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, Machines and Control (PEMC) Research Institute , University of Nottingham. The project will be supported by the state-of-the-art electric motor manufacturing platforms at both locations. Project Description
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within the climate change domain. The techniques are based on statistical and computational approaches, including machine learning algorithms. The project aims first to contribute to the prevention of fake