204 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"IFM" PhD positions in United Kingdom
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for research into thermal management and system health monitoring, supporting studies in military aircraft systems. Engaging with these facilities allows students to acquire practical skills and technical
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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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- 2025 - Business Strategy and the Environment - Wiley Online Library Additive Manufacturing: A Comprehensive Review Big data, machine learning, and digital twin assisted additive manufacturing: A review
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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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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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Wales, meaning most paediatric records are handwritten and unstructured. The project will prioritise digitising these records using natural language processing (NLP) and machine learning (ML) to create
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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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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