25 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "Ulster University" PhD positions at Cranfield University
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this issue and we could use obtain data-driven models using machine learning algorithms such as artificial neural networks, reinforcement learning, and deep learning. A typical caveat of data-driven modelling
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Fibre reinforced composites have excellent in plane strength and stiffness and are being used in increasing quantities in aerospace, sports, automotive and wind turbine blade industries. However fibre reinforced composites are weak in their through thickness direction. This weakness can result...
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industrial partners, such as WAAM3D (https://waam3d.com/ ) and members of WAAMMat (https://waammat.com/ ), gaining valuable industry experience and exposure. The student is expected to acquire the following
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of WAAMMat (https://waammat.com/ ), gaining valuable industry experience and exposure. The student is expected to acquire the following (including but not limited to) knowledge and skills from the research in
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This research opportunity invites self-funded PhD candidates to develop advanced deblurring techniques for retinal images using deep learning and variational methods. Retinal images often suffer
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diagnosis and prognosis technologies, and, consequently, improve maintenance decision making. Currently, machine learning exists as the most promising technologies of big data analytics in industrial problems
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health monitoring, supporting studies in military aircraft systems. Engaging with these facilities allows students to acquire practical skills and technical expertise, enhancing their research capabilities
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failures before they occur, enabling proactive maintenance strategies. Anomaly Detection Mechanisms: Implement machine learning techniques to identify and classify anomalies in electronic systems, enhancing
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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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, supporting studies in military aircraft systems. Engaging with these facilities allows students to acquire practical skills and technical expertise, enhancing their research capabilities and employability in