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challenging properties of uncertainty, irregularity and mixed-modality. It will examine a range of models and techniques that go beyond Markovian approaches, including state-space models, tensor networks, and
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Supervised by: Rasa Remenyte-Prescott (Faculty of Engineering, Resilience Engineering Research Group) Aim: Develop a mathematical model for obsolescence modelling for railway signalling and telecoms
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in healthcare service and opportunities for identification of such deviations using computer vision approaches. It will demonstrate how deviation data can be used in computer-based simulation models
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of mechanical and robotic systems •Ability to use finite element modelling and to simulate complex mechatronics •Ability to implement control and kinematics with hardware-in-the–loop •Background with relevant
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Dr Sendy Phang. The student can gain experience and skills in a range of topics, such as Artificial Intelligence and Deep Learning, nanofabrication, computational modelling, metamaterial design, and
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Dr Sendy Phang. The student can gain experience and skills in a range of topics, such as Artificial Intelligence and Deep Learning, nanofabrication, computational modelling, metamaterial design, and
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for the project will include: A thorough review of (1a) interface capturing approaches for flow boiling simulations including adaptive mesh refinement, (1b) available models for predicting the density of nucleation
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information or questions about this PhD please contact nicola.love@ukhsa.gov.uk . To be considered for this PhD please send a copy of your CV and a personal statement up to 500 words explaining your suitability
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determine the impact of community acquired pneumonia that requires hospitalisation has on the quality of life of patients. The final stage will be to design a generic economic model to evaluate any new
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Research Groups at the Faculty of Engineering, which conduct cutting-edge research into electric propulsion systems, composite materials, and advanced simulation technologies. Vision We are seeking a highly