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machine learning, spatial audio and audio-visual AI into groundbreaking creative technology. About you We seek a talented Research Fellow to investigate generative audio AI technology for production
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to gain academic research experience and to learn from leading academics. The ideal candidate for this role will have a background in qualitative social science research, such as literature reviews, surveys
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contributory pension scheme 38 days annual leave A comprehensive range of childcare services Family leave schemes Cycle and electric car loan schemes Employee Assistance Programme Membership to a variety of
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willingness to learn new skills and undertake further training and development aligned to the role, which may include working with laboratory animals Experience in working in a scientific laboratory, including
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) in Physics or a related field. Previous experience in cosmological simulations, analysis of cosmic microwave background and/or large-scale structure datasets, machine learning methods applied
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al. (2024) Photonics for Neuromorphic Computing: Fundamentals, Devices, and Opportunities. Advanced Materials. doi: 10.1002/adma.202312825. [6] K. Lee et al., “Secure Machine Learning Hardware
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Python and C++ with relevant computer vision, signal processing, machine learning and/or deep learning tools (TensorFlow, PyTorch, Keras, OpenCV etc.). A track record of publishing academic papers, open
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vision systems addressing an urgent industrial challenge with immediate, large-scale impact. The project will take existing knowledge in computer vision and deep learning and apply it directly to a
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the area of quantum machine learning. You will engage in advanced study and academic research, working to develop and carry out research projects, teach and co-supervise graduate students, and contribute
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viewing conditions and across languages. By combining behavioural methods with machine learning, it aims to develop physiologically-based models of lexical colour categorisation. This is a multidisciplinary