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Field
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to an evaluation of how user-friendly and acceptable an AI-powered dashboard is among registered nurses (RNs) caring for patients having colorectal surgery. This is a six-month multisite study funded by the AI
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it relates to the laser process parameters. Specifically, you will carry out high resolution Raman imaging on laser written polymer networks with liquid crystal resins. Additionally, you will develop
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; experience of working on biological systems and/or craniofacial system; experience in image processing and material characterisation. The post is initially funded for 3 years and will be subject to standard
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identify new drug targets. The project will involve advanced histological, biochemical and molecular approaches. You will be responsible for collection, processing, analysis, presentation (writing, graph
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techniques, most notably protein crystallography, cryo-electron microscopy, DNA sequencing and monoclonal antibodies. The LMB has a clear goal of understanding biological processes at the molecular level, with
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understanding of the polymer network morphology and how it relates to the laser process parameters. Specifically, you will carry out high resolution Raman imaging on laser written polymer networks with liquid
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: Essential criteria PhD qualified in relevant subject area (Immunology, Biophysics, Biochemistry, etc) * Expertise in biomechanics, both the theory and methods Expertise in T cell biology, immunology, cancer
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Resonance Imaging (MRI). This post also be linked to research activities linked to the University’s research platforms such as the UNNC Sir Peter Mansfield MRI Centre. Candidates must have a PhD degree in the
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potential applications in audio and music processing. Standard neural network training practices largely follow an open-loop paradigm, where the evolving state of the model typically does not influence
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Cranfield University invites applications for a PhD funded by Thames Water through the Ofwat Innovation Fund. The studentship covers full Home tuition fees plus a tax free stipend of £24,000 per