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subsurface and internal temperature distributions. Semi-destructive approaches, such as embedding thermocouples by drilling holes, can provide internal data but often disrupt the process, alter the thermal
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considered. Experience of using machine learning algorithms and toolsets, ideally in a research context. Strong programming skills (e.g., Python, Java, C++). An interest in physiological signals. Home Student
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relationship between brain structure, myelin distribution and genetic factors in MS. Research Focus: Recently, computational pipelines have been developed to integrate genetic and imaging databases
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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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) of high-value critical assets. Through this PhD research, algorithms and tools will be further improved and developed, validated and tested. It is expected that combining the domain knowledge and the
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memorisation capabilities of deep learning models. Such vulnerabilities expose FL systems to various privacy attacks, making the study of privacy in distributed settings increasingly complex and vital
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allow you to explore the fundament physical limits of the technique and to create new image reconstruction algorithms. This project offers the opportunity to produce new techniques in imaging physics
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, distributed ledgers) Desirable: Experience with generative AI (e.g. LLMs) Interest in Human-Computer Interaction Interest in privacy enhancing technologies (PETs) Other: Experience in presenting or preparing
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1 and 2 and NQCC Testbed programme, will tailor the developed benchmarking approaches to error-corrected as well as distributed quantum computers, addressing the need for scalable benchmarks
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Physics graduates with a strong background in Fluid Mechanics and Heat Transfer. The work will involve the use of flow diagnostics techniques and post-processing algorithms. It will also require