38 medical-image-processing-artificial-intelligence PhD positions at University of Nottingham
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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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dealing with investigations on the development of bespoke high-tech laser beam processing methods for surface treatment and repair of aero-engine components. The project will deal with the study of a new
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excellence, developing and applying innovative research in Artificial Intelligence (AI) and Human Behaviour in projects targeting social good. Research at N/LAB focuses on the development and application
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Manufacturing process for Cold Spray with Artificial Intelligence, operate the AM machine, characterise the materials with scanning electron microscopy and transmission electron microscopy with tensile testing
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of real-time digital twin (physical or Artificial Intelligent based) of electric propulsion system including propulsion motors, power converters, fuel cell and batteries etc within the real-time simulation
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research programme funded by the Academy of Medical Sciences Springboard award. This project aims to explore the role of these neighbouring glycoproteins in neurotrophin-mediated neuronal development as
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highly efficient operation. TBCs are crucial to ensure the safe and high-performance operation of such critical parts under extreme temperatures and pressures; however, external contaminants (e.g. Calcium
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with participants to deliver measures concerning people’s experiences of the diagnostic process, their access to services and their general well-being and life quality. The positions are ideal for people
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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 supportive lab culture with
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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