215 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:" PhD positions in United Kingdom
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Field
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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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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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, adaptive control strategies, and hybrid energy storage solutions to address key challenges in self-powered systems under dynamic environmental conditions by: Develop machine learning or heuristic-based
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and architectures that support efficient, secure, and scalable machine learning operations (MLOps) across resource-constrained environments for Edge AI. Ethical, and responsible FL for healthcare: In
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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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The accuracy and precision of opto-electronic 3D motion capture systems created a global shift towards lab-based biomechanical analysis over the last 30 years. With the advent of AI and machine
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high 2:1 in computer science, mechanical engineering, or aerospace engineering. You should have programming experience applied to physics/engineering problems and/or experience with machine learning and
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establish a digital route to quantify the segregation behaviour of residual elements at austenite/austenite grain boundaries through atomic-scale simulations, using modern machine learning techniques and in
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sensors - if we can control and tune their properties. You will develop and use top-of-the-line machine learning models to predict the sensor response of these materials under realistic conditions
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Super-Resolution Radial Fluctuations (SRRF) approach. The objective is to build machine-learning models that exploit the underlying physics of fluorescence fluctuations to deliver high-resolution, low