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studies, sociology, & digital humanities. They should also be prepared to undertake substantial interaction with computer science and other technical disciplines as appropriate, and to engage in
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. Simulations are suitable to characterise processes in healthy and diseased individuals including stroke patients. Machine learning methods might be considered to accelerate simulations. The project provides a
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programme +2 - covering 2 years of study for current postgraduate researchers 1+3 - covering Master's and Doctoral study Please see Additional Information for 1+3 and +2 application processes. Tenable period
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pressure waveforms. The PhD student will exploit a combination of digital image correlation (DIC) and particle image velocimetry (PIV) methods to robustly characterise the biomechanical behaviour of the HVs
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performance simulation capabilities for gas turbine engines developed at Cranfield University as the starting point. Applications are invited for a PhD studentship in the Centre for Propulsion and Thermal Power