383 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Simons Foundation" PhD positions in United Kingdom
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Field
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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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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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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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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
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
intelligence, particularly in computer vision and deep learning, offer an opportunity to automate and enhance damage assessment by learning patterns from multimodal data. This research seeks to bridge the gap
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CFD, thermofluids and machine learning. Experience in Python (or another language), machine learning frameworks, or CFD tools such as OpenFOAM is beneficial but not required. Applicants should hold (or
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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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of lightweight, logic-based machine learning approaches. In addition, agents must support collective decision-making to achieve system-wide optimisation rather than isolated, local improvements. Finally
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, stiffness loss, damage evolution, and transient creep interact under coupled loading. The project will develop temperature-dependent constitutive models informed by numerical simulation. Machine learning
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machine learning techniques, you will identify patient subgroups, improve diagnostic accuracy, and develop a biomarker-based clinical decision support system to assist risk stratification and outcome