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students and an annual stipend equivalent to current UKRI rates. Key words: Brain cancer, glioblastoma, magnetic resonance imaging, advanced MRI, radiomics, machine learning. View All Vacancies
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imaging features to phenometabolic signatures from tissue samples taken during surgery and matched to the imaging. The project is part of the imaging theme for the new Nottingham Brain Tumour Research
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into the sample of interest. Recently we have been using AI and machine learning to predict the distortion present and significantly speed up this correction process. This PhD project will take the latest in AI
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. What you should have: A 1st degree in physics or engineering. An interest in optics, some ability in computer programming A desire to learn new skills in complementary disciplines. You will work jointly
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using multimodal approaches including advanced imaging, nano-mechanical characterisation and machine learning techniques Developing physics-informed reliability models using experimental datasets
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-resolution (SR) technologies influence human and machine-based facial identification. The PhD will combine behavioural experiments, machine learning, and explainable-AI methods to answer questions: 1. Do SR
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. The PhD will combine behavioural experiments, machine learning, and explainable-AI methods to answer questions: Do SR techniques improve human face identification accuracy? How do SR-enhanced images affect
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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
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Bachelors Honours degree (or equivalent) in an appropriate discipline. Ideal candidate will have some prior knowledge in deep learning and computer graphics. Subject Area Medical imaging, biomedical
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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