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This is an exciting PhD opportunity to develop innovative AI and computer vision tools to automate the identification and monitoring of UK pollinators from images and videos. Working at
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
developed a dataset by conducting high-velocity impact experiments on CFRP specimens using controlled testing setups. The multimodal dataset is to be processed using X-ray CT scans, SEM imaging, and
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slow sand filters. This project suits graduates seeking careers in drinking water technology, sustainable infrastructure, and low carbon process design. Drinking water production is under mounting
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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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technologies. Metamaterials, engineered to exhibit properties not found in naturally occurring materials, offer an innovative pathway to overcome these limitations. By designing intricate periodic or quasi
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Technology Centre (DARTeC), leading advancements in aircraft electrification, autonomous systems, and secure intelligent hardware. Through collaborations with the Aerospace Integration Research Centre (AIRC