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on operations. To support development of complex multi-layered systems and to inform rapid decision-making, this project will develop advanced Machine Learning (ML) architectures that learn directly from a
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Deadline for applications: 15th of April 2024 (or until the position if filled) One fully funded PhD position to work with Dr Milos Nikolic in the School of Informatics at the University
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signal processing or machine learning technologies will be considered, as well as specific technical challenges. For example, projects in this theme will consider aspects related to: wide area motion
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an ongoing collaboration with researchers from UCL and the University of Edinburgh. For additional information, please contact Dr Xi Wang at [email protected]. When reaching out, kindly use the subject
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University of Edinburgh. For additional information, please contact Dr Xi Wang at [email protected]. When reaching out, kindly use the subject line '[PhD-Sim4Conv] - [Your Name] - [Your Current
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the Advanced Care Research Centre (ACRC) at The University of Edinburgh and be at the forefront of innovative solutions for promoting healthy ageing and future care for people in later life. You will
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machine learning solutions to enhance performance and develop novel hardware/software co-designed sensing systems. However, in defence scenarios it is vital that verifiable algorithmic solutions are used
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part in teaching and student supervision activities in areas related to your expertise; What do we require? A PhD degree (or equivalent qualification) in AI (e.g., machine learning, natural
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to your expertise; What do we require? A PhD degree (or equivalent qualification) in AI (e.g., machine learning, natural language processing or computer vision); A strong scientific track record, documented
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is hypothesised to exert an additional stress on the bubble surface, however, its exact effect on the nanobubble’s cavitation dynamics is still unexplored. In this PhD project, you will develop new