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                We invite applications for a PhD project focused on fundamental research into novel low-emission ammonia combustion/oxidation processes. This position is based within the Faculty of Engineering at 
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                AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhDintelligence, particularly in computer vision and deep learning, offer an opportunity to automate and enhance damage assessment by learning patterns from multimodal data. This research seeks to bridge the gap 
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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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                principles, lab measurement, computer vision and ArcGIS, potential fieldwork and UAV flying training. Person specification Experience and/or enthusiastic interest in one or more of the following areas 
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                PhD in Computer Science: Sustainable AI for Plant Species Recognition in Tropical Forests School of Computer Science PhD Research Project Directly Funded Students Worldwide Dr Jefersson Alex dos 
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                https://www.sems.qmul.ac.uk/research/studentships/674/net-zero-natural-resource-energy-and-time-efficient-manufacturing/The PhD work will benefit from access to unique facilities including 
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                to completion of the PhD programme. The DTP will reserve up to 3 ring-fenced scholarships for home students from certain Black, Asian & Minority Ethnic groups. The eligibility criteria for these ring-fenced 
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                ’. Warwick University is renowned for its high-quality research and a thriving PhD program. This strong research culture enhances both the PhD student’s experience and the demand for our graduates. This PhD 
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                Deadline: 30 September 2025 A fully funded 3.5 year PhD position is available to work on the project titled “Scalable benchmarking for digital quantum computers based on blind testing 
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                This self-funded PhD opportunity explores assured multi-sensor localisation in 6G terrestrial and non-terrestrial networks (TN–NTN), combining GNSS positioning, inertial systems, and vision-based