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techniques, data analysis with desirable knowledge of material characterisation, rheology and imaging. Scientific interest, dedication to research and career goal to work in physical science research
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& Statistics Project description Unmanned Aerial Vehicle (UAV) e.g., drones are increasingly used for equipment anomaly and fault detection. When the drones are employed to take images, the quality of the images
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will lead to natural collaboration opportunities. The primary methods used in this project will be experimental, involving fluid characterisation and high-speed imaging experiments, using Phantom high
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imaging data and possess sufficient specialist knowledge in brain imaging. The position is full time (part time considered) fixed term for two years. The closing date for applications is noon on 21 April
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will hold a relevant PhD/Dphil in statistics, machine learning or similar area, together with relevant experience working with brain imaging data and possess sufficient specialist knowledge in brain
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will use the Residential Anonymous Linking Field (RALF), an encrypted Unique Property Reference Number (UPRN) which has been used in SAIL since 2012, to enable household level data linkages which will
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purification is desirable but not necessary. Candidates with physics and physical chemistry are encouraged to apply. Knowledge of coding and image analysis is desirable but not necessary. As well as supporting
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We are offering a fully-funded PhD studentship working at the interface of photonics, robotics and fusion research. The project is focussed on the development of new imaging technologies to enhance
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mixture ratio has an impact on the performance of the hybrid propellant propulsion system making it hard to optimise. Work at Kingston University has been on the development of imaging techniques using
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Nikon Imaging Centre (The Wohl Cellular Imaging Centre), are part of the UK Motor Neuron Disease Research Institute and work closely with researchers in the UK Dementia Research Institute. Dr Sreedharan