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Machine Learning techniques to this data to extract the essential information contained within these trajectories. This will be achieved through the following steps: Develop tools to efficiently generate a
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Project title: Machine Learning models for subgrid scales in turbulent reacting flows Supervisory Team: Temistocle Grenga, Ed Richardson Project description: Supervised deep convolutional neural
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, more agile solutions. Current machine learning (ML) algorithms identify and predict threats but rely heavily on past datasets, requiring significant updates. Continual learning offers a solution by
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for you to be exposed and trained to handle the interdisciplinary challenges faced in the real-world via a Systems Thinking approach. You will learn about the wider challenges of research and innovation
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model reconstruction. Supervisor Associate Professor Hansung Kim Vision, Learning and Control Research Group School of Electronics and Computer Science, University of Southampton http://www.3dkim.com/Eng
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adversaries might exploit quantum technology. In this project, you will conduct an in-depth threat analysis of quantum-computer attacks on cyber-physical systems, considering system configurations, data
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PhD Supervisor: Dr Marcus Newton Supervisory Team: Dr Marcus Newton, Dr Dan Porter, Prof Steve Collins, Prof Paul Quinn Project description: The University of Southampton is expanding its PhD
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, Signal Processing, Machine Learning, or Computer Science. We welcome applicants onto the CDT from underrepresented groups. Closing date : 31th Aug 2024. Funding: Full-time studentships will cover UK
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students, including Bursaries and Scholarships. For more information please visit PhD Scholarships | Doctoral College | University of Southampton Funding will be awarded on a rolling basis, so apply early
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University Guide 2022) within the University of Southampton which is ranked in the top 1% of universities worldwide. The successful candidate must have a strong background in machine learning. Prior knowledge