38 medical-image-processing-artificial-intelligence PhD positions at University of Nottingham
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Master in Epidemiology or Public Health with experience in medical statistical analyses, an understanding of Health Economics, knowledge of the strengths and weaknesses of scientific research, excellent
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suitable for a hard-working researcher with an interest in respiratory infections. Essential skills: A BSc degree or equivalent ideally in a health related field, excellent computer literacy, good inter
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portfolio, conducts cutting edge research into the development of future Intelligent Reconfigurable Manufacturing Systems. This is 3-year fully funded studentship and is only open to UK home students. The
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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 tools (Ansys, JMAG, .etc) and programming are desirable. Experience in electrical machine prototype development would be advantageous. Eligibility and Application
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of such posts include clinical, medical and allied health roles, roles involving childcare services. A DBS check may also be required. The University will only use information relating to criminal convictions
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for medical applications, micro-robotics, and materials science. PhD project description: The field of medical therapeutics has valuable applications for mobile devices for efficient drug delivery, called micro
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or joining thin-wall Titanium and Nickel alloys at high temperatures. Due to the unique material behaviours of these sheets and foils (0.1 mm to 0.5 mm thick), controlling variables in the forming process is
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this advanced manufacturing process will open new opportunities: devices with variable mechanical and chemical properties; fully 3D-printed electronics; and devices with mechanical or electrical responses encoded
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enhance system reliability and safety, aligning with the UK’s NetZero targets. Aim You will have the opportunity to build a high-fidelity process simulation and perform experimental validation to assess