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Field
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viscous and elastic properties. These fluids are fundamental for a myriad of industrial processes (such as mixing of chemicals or cooling of microprocessors), however they are still not well understood due
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. Through simulation and controlled experiments, we aim to assess the performance of these systems in tasks such as structural inspections, debris removal, and repairs. Additionally, we will evaluate
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desirable Downloading a copy of our Job Description Full details of the role and the skills, knowledge and experience required can be found in the Job Description document, provided at the bottom of the next
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metrics during both standard operation (primarily governed by system reliability) and extreme events (primarily governed by robustness and restoration). This will be achieved by building on previous
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direction could be to use the technique of Inverse Reinforcement Learning (IRL) [2], [3]. IRL is an AI-based technique that supports imitation of the preferred system behaviour by using its behavioural
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simulating fluid networks and dynamic phenomena for assessing different solutions is a necessity The overall aim of this project is to improve the confidence in fuel system design process for ultra-efficient
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communications in smart manufacturing. We are seeking an ambitious and technically capable individual with a strong academic background in Computer Science, Computer Networking, Telecommunications, or a closely
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overseas equivalent) Nationality restrictions This funding is available to all nationalities. Application procedure You must submit your completed online programme application for a place on your chosen PhD
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tools. Experience in microscopy, preferentially confocal imaging Downloading a copy of our Job Description Full details of the role and the skills, knowledge and experience required can be found in
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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