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Field
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Embark on a ground-breaking PhD project harnessing the power of Myopic Mean Field Games (MFG) and Multi-Agent Reinforced Learning (MARL) to delve into the dynamic world of evolving cyber-physical
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prototype/demonstrator of a low-cost smart sensor. To develop an efficient algorithm to process the vibration signals locally and to develop the firmware to be embedded within the sensor node. To validate
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internships An additional disability allowance can be provided where appropriate Students opting to study part-time will receive a pro-rata maintenance stipend. Specified use +3 - covering a full PhD programme
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exhaustive, and the PhD candidate will be required to undertake such tasks and responsibilities as may reasonably be expected of a PhD candidate. Application process The application should include: a
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, this interdisciplinary project will couple mathematical models of earthworm movement, stochastic models of the measurement process and designed experiments to improve earthworm detection. Project This project will work
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the foundation of computer vision, monitoring, and control solutions. However, real applications of AI have typically been demonstrated under highly controlled conditions. Battery assembly processes can be
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programme that was taught and examined in the medium of English, the minimum overall IELTS score is 6.5 with no score lower than 6.0 in Reading, Writing, Speaking and Listening. Please note that possession
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of the project is to 1) develop computational pipelines for image analysis and physical analysis of cell shape trajectories, and for combined morpho-molecular analysis of cell shape together with molecular markers
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PhD level in an appropriate discipline, and you will have sufficient breadth or depth of knowledge in physical acoustics and information theory. You will have knowledge of appropriate research methods
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interview process. RCUK eligibility: No Eligibility: Strathclyde Business School is committed to supporting a diverse and inclusive postgraduate research population. We make decisions on entry by assessing