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to produce anti-counterfeit markings, dye-free colour images, humidity and chemical sensors, anti-glare coatings and optical filters. This project will develop additive manufacturing of devices with actively
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with coding, ideally in Python or MATLAB Funding support This studentship is open to Home students only. It is jointly supported by the Faculty of Engineering and industrial partners which is expected
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identifying relevant treatments and their associated Health Resource Group (HRG) codes to link hospital care provided with NHS Reference Costs, as well as linking any primary care activity with Unit Costs of
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. cell culture, molecular biology, imaging, cell signalling assays). As well as performing experiments on the project, the role will involve providing training in techniques to relevant staff/students
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-derived criteria. A scoping review, alongside initial semi-structured interviews and focus group transcripts subjected to thematic analysis, will build a picture of what key stakeholders want. Clinic
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Environment: Based at the Biodiscovery Institute at UoN, a multidisciplinary centre with advanced laboratory and imaging facilities Access to a full range of equipment and laboratory facilities. Inclusive and
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engineering. Expertise in numerical electrical machine design tools (Ansys, JMAG, .etc) as well as corresponding scripting skills are desirable. Experience in electrical machine prototype development would be
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engineering. Expertise in numerical tools (Ansys, JMAG, .etc) and programming are desirable. Experience in electrical machine prototype development would be advantageous. Eligibility and Application