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The University of Surrey is offering a fully funded PhD studentship on the topic of Audio/acoustics machine learning for intelligent sound reproduction, with industrial partner Bang & Olufsen
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One PhD studentship is available in the area of machine learning theory (statistical learning theory and deep learning theory) or theoretical-oriented topics, e.g., trustworthy machine learning
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implementation of position location estimation using Machine Learning (ML) techniques has been proposed as a methodology to improve performance beyond that of existing techniques, particularly in non-line-of-sight
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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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Overview About the Role Applications are invited for a motivated and committed Machine Learning Engineer. The successful candidate will contribute to Queen Mary’s national reputation for research by planning
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machine-learning techniques in ST studies. Our approach introduces two innovations: developing sparse Bayesian learning algorithms for efficient small dataset analysis and designing a simulator for
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About the Role Applications are invited for a motivated and committed Machine Learning Engineer. The successful candidate will contribute to Queen Mary’s national reputation for research by planning
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The University of Surrey is offering a fully funded PhD studentship on the topics of Deep Learning for Audio-Visual Scene Analysis, with industrial partner Bang & Olufsen. This project aims
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make informed decisions.. Join our dynamic interdisciplinary group and lead pioneering research to develop novel machine learning algorithms specifically designed for complex systems analysis. Your role