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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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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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to Postdocs, Research Assistants, Research and Teaching Technicians, Teaching Fellows and AEP equivalent up to and including grade 7. Visit the Centre for Research Staff Development for more information. About
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Project summary: A transition to net zero is desirable overall, but its costs and benefits are unevenly distributed across time, space, and between individuals, and policy to implement it must be
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novel sensing approaches to combine with machine learning algorithms to solve real-world problems in food manufacturing. You will have sound knowledge in electronic engineering, embedded systems design
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workspaces under positional restrictions. Develop smart control algorithms that will allow the robotics end-effectors to communicate with the central control system and coordinate tasks with other end
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microbial communities. In this role, you will develop hybrid species distribution models that combine climate and landscape data to predict how microbial taxa niches shift under changing land use and
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the availability and distribution of shaded pedestrian routes in Reading, with the aim of identifying priority areas for shade provision to support equitable and heat-resilient urban mobility. Green infrastructure
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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