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Deadline: 7th January 2026 One fully funded, full-time PhD position to work with Dr. Viacheslav Borovitskiy in his new research group at the School of Informatics, University of Edinburgh. Our
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Technology, The University of Nottingham. Applicants are invited to undertake a three-year PhD programme in partnership with industry to address key challenges in on-platform manufacturing engineering. The
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research. Specific multidisciplinary skills include: synthetic chemistry, structural molecular biology and advanced imaging; it will harness cutting edge computational tools (incl. image analyses), giving
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PhD studentship: Improving reliability of medical processes using system modelling and Artificial Intelligence techniques Supervised by: Rasa Remenyte-Prescott (Faculty of Engineering, Resilience
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autophagy and the innate immunity response. Using cutting-edge omics (transcriptomics/proteomics), advanced imaging (confocal) and cellular biology approaches (macrophages, autophagy biomarkers), this project
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editing), transcriptomics, laser scanning confocal microscopy, computational imaging approaches for analysis of images and movies, stimulating neuronal function with opto- and thermo-genetics in vivo, and
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PhD Studentship: Rolls-Royce Sponsored PhD Scholarship – Micromechanics and In-Depth Materials Analysis of Advanced Aerospace Materials Upon the Manufacturing Process Engineering Applications
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Are you ready to push the boundaries of engineering innovation and accelerate the world’s transition to carbon-neutral energy systems? Join the Thermofluids Group in the School of Mechanical
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Applications are invited to undertake a three-year PhD programme in partnership with industry to address key challenges in manufacturing engineering. The successful candidate will be based
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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