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MEng degree in Electrical and Electronics Engineering or Aerospace Engineering. To apply or for further information, please contact Dr Sharmila Sumsurooah Sharmila.Sumsurooah@nottingham.ac.uk Funding
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to the interests of one of the School’s research groups: Cyber-physical Health and Assistive Robotics Technologies Computational Optimisation and Learning Lab Computer Vision Lab Cyber Security Functional
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theory, robust and optimal control, and physics-informed modelling, this research aims to bridge the gap between data-driven learning and dependable real-world autonomy. Aim You will have the opportunity
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orla.williams@nottingham.ac.uk for more information Funding support After a suitable candidate is found, funding is then sought from the University of Nottingham as part of a competitive process (this will cover
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mechanics. Skills you’ll gain Under the supervision of Charlie Heron and myself you will gain: Expert knowledge of centrifuge modelling challenges and solutions. Advanced programming/data analysis skills. How
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of experimental modelling challenges and solutions. Advanced programming/data analysis and simulation skills. How to effectively communicate complex and novel research. Opportunities to develop lab demonstration
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-edge adaptive mesh refinement techniques; a lightweight prediction tool developed upon the simulation data to predict key thermofluidic parameters for the design of high heat flux cooling components
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) and X-ray absorption techniques. The student will also gain experience in using ultra-high vacuum apparatus, data processing and scientific programming, as well as training in more general skills such