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the VR viewer's point of view, and manually coding VR events and the participant behavioural response. This project focuses on automating this process through the training of AI models to detect
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Large language models increasingly adapt using external feedback to alter inference-time behaviour, persistent state or model parameters. However, the signals that drive these changes may be noisy
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act as the senior escalation point during major cyber incidents, providing coordination, communication, and executive-level decision support. At the same time, you will own the end-to-end performance
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project management, stakeholder collaboration and a deep understanding of what drives audience engagement. You’ll also be a central liaison point between the Campus Experience and Major Events team
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the development of project documentation, reports, briefings and presentations. This role will also act as a key liaison point for project progress and objectives, providing sound and timely advice
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This project involves the automated generation of textual descriptions for audio content, such as spoken language, sound events, or music. This process typically employs deep learning techniques
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while inferring underlying physiological changes. Required knowledge Machine learning, dynamical systems theory, control theory, signal processing, time series analysis, neuroscience are all relevant and
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offerings and functions, including (but not limited to) membership sales and renewals, Point of Sales (POS) transactions, and casual court hire bookings. Health and Fitness Instructor essential requirements
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background in AI/ML, data science, or signal processing Interest in music informatics, emotion modelling, or multimodal AI Ability to implement and evaluate machine learning models independently Commitment
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funding opportunities to facilitate the growth of the Faculties research performance. You will act as a key liaison point, working closely with senior academics including the Heads of Department, Directors