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methodology to generate confidence in such decision, potentially reducing maintenance costs and down-time for offshore wind energy production. The images taken by each drone are loaded into the pre-processing
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A competition-funded PhD studentship is available in the School of Chemistry at the University of Birmingham to develop and apply nuclear magnetic resonance spectroscopy and imaging to advance
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and technology. Desirable (not essential): Research experience in sports medicine and technology (e.g. publication or final year project). Programming skills in MATLAB or Python. Application Procedure
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Mativenga (UoM), has extensive expertise in laser materials processing. Dr Chu Lun Alex Leung (Mechanical Engineering at UCL) will also collaborate. he specialises in imaging of additive manufacturing and
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Join an exciting research journey at the intersection of advanced materials, electronics, and textile engineering. This PhD project will explore smart structural design, manufacturing and
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(computer vision technologies). The interdisciplinary nature of this PhD will require the integration of environmental science, engineering, and community science methodologies. Supervisors: Primary
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benefit from the extensive and broad expertise in AI and biomedical computing at the School of Biomedical Engineering & Imaging Sciences. The work will be done in close collaboration with a
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imaging and monitoring of resin infusion in sample composite structures to build the digital twin and then explore methods for defect prediction and real time process control. The improved process
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will also work closely with our industrial partner on process engineering for a scalable prototype facility and product output testing. The successful PhD student will be supervised by Prof Anh Phan from
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expertise in AI and biomedical computing at the School of Biomedical Engineering & Imaging Sciences. The work will be done in close collaboration with a multidisciplinary team at KCL, UCL and with clinicians