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Applications are invited for one full-time EPSRC Industrial CASE (ICASE) PhD studentship for each project. “Development of natural-ageing-resistant, heat-treatable lean aluminium alloys
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aims: Develop end-to-end protocols for screening selected foods and nutraceuticals. Create advanced strategies for data integration using tailored algorithms and machine learning approaches. Demonstrate
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specifically addresses the identified challenge by leveraging ML to overcome barriers associated with platform heterogeneity, including differences in resolution, scale, and feature representation. By developing
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vulnerabilities like side-channel attacks and unauthorized access, which can compromise system integrity. Developing robust security measures within AI-enabled electronics is essential for applications in defence
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and misalignment, facilitating the development and validation of diagnostic and prognostic algorithms. Electronic Prognostics Systems: Facilities equipped to assess the health and predict the remaining
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This research opportunity invites self-funded PhD candidates to develop advanced deblurring techniques for retinal images using deep learning and variational methods. Retinal images often suffer
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opportunities to address critical challenges in modern society. A shining example of this was the COVID-19 vaccines. Nanotechnology is key to achieving the UN Sustainable Development Goals. As such, key
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techniques, would be an advantage. The ideal candidate will have a deep interest in the algorithms that power graphics and a creative mindset, eager to think outside the box and develop novel solutions
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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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Havoutis Year 1 MSc Course: MSc Robotics Year 2 – 4 PhD Location: Oxford University Research Abstract: This PhD project will focus on developing an AI-based system for multi-collaborative scouting and