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to achieve, at least a 2.1 honours degree or a master’s in a relevant science or engineering related discipline. Applicants should have strong background in Machine Learning and Deep Learning. To apply, please
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should have a strong foundation in artificial intelligence, machine learning, and multi-agent systems, along with experience in programming, data analysis, and model development. Knowledge
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We are pleased to announce PhD studentship project in “Advanced Composites Development for Hyper-velocity Impact Protection of Space Satellites Structures”. This is an exciting PhD research
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established methods of microstructural analysis and mechanical testing with new schemes such as Acoustic Emission for non-destructive assessment of degradation and Machine Learning for development of predictive
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learning. The project involves a collaborative team, including a postdoctoral researcher and a PhD student, with specific objectives: Define and acquire a comprehensive database of high-quality video priors
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Supervisory Team: Leonardo Aniello, Han Wu PhD Supervisor: Leonardo Aniello Project description: Blockchain and Federated Learning (FL) are two emerging technologies that, when combined, offer a
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Machine Learning-based diagnostics and prognostics digital twin system will be developed, aiming to provide fast and reliable predictions of the health of gas turbine engines. Non-confidential operational
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in computer vision would be beneficial but not essential; determination, curiosity, and a willingness to learn are key attributes we value. Applicants with alternative qualifications, industry
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, these systems serve as complex functional approximators trained over an input-output data set. ‘Second Wave AI’ is the term used to describe the current glut of 'machine learning' style intelligence, where
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this issue and we could use obtain data-driven models using machine learning algorithms such as artificial neural networks, reinforcement learning, and deep learning. A typical caveat of data-driven modelling