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Field
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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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thermodynamically. Performance design optimization and advanced performance simulation methods will be investigated, and corresponding computer software will be developed. The research will contribute
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through the following objectives: Develop a novel approach to investigate the fluid-solid coupling effect on the performance of the CMF; Using machine-learning (deep learning) methods to develop a
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to complex challenges in this field. Essential and Desirable Criteria Solid foundation in computing principles, particularly computer graphics and machine learning. A 1st or 2.1 undergraduate (BEng, BSc, MEng
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to machine learning and deep neural networks, into the DG finite element solver to reduce computational costs while maintaining the accuracy. The key objective of this work will be to provide step-change
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Provide human experts with a reliable second opinion This project integrates image processing, data analytics, machine learning, and computational modelling, with applications in aerospace, mechanical
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science, along with proven skills in prototyping software using real-time 3D engines and implementing machine learning models. With 50+ researchers and PhD students, the Centre for Sustainable Cyber Security (CS2
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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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(or equivalent) in an appropriate discipline. Ideal candidate will have some prior knowledge in deep learning and computer graphics. Subject area: Medical imaging, biomedical engineering, computer science & IT
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cobalt-free cathodes. The project can involve aspects of materials synthesis, x-ray diffraction and crystallography, scientific software development and machine-learning enhanced analysis depending