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and accuracy, ultimately saving lives. This collaborative PhD project aims to develop and evaluate advanced deep learning models for speech and audio analysis to predict Category 1 emergencies
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(KCL, London, UK) but will also have the opportunity to travel and work at the Centre for AI and Machine Learning (ECU, Perth, AU) and the School of Psychiatry and Clinical Neuroscience (UWA, Perth, AU
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in machine learning and/or computer security and Experience working with LLMs or agent-based systems. Informal enquiries may be addressed to adel.bibi@eng.ox.ac.uk For more information about working at
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of how this machine functions. Elucidating the function is key to unlocking why certain mutations can cause disease such as early onset cardiac disease (through the muscle myosin protein) and how small
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scales, lubrication and wetting, biophysics as well as machine learning or metamaterials. For experimentalists, we particularly interested in applicants aligned with our existing research infrastructure
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. This role will be engaged in the development of educational thinking, practice and research in the broad areas of curriculum design, learning and teaching, and assessment. As well as this, the successful
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experience in astronomical data analysis activities, coupled with use of machine learning approaches to data validation, a good practical knowledge of scientific algorithm development and a PhD degree in a
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experiments, algal bioprocess modelling and optimisation, machine learning and data-driven modelling, and business case development, ensuring the technology is optimised for deployment across diverse industrial
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PhD qualified in mathematical, physical or computational sciences Experience in using machine learning methods to analyse datasets Experience in statistical or scientific programming (ideally R and/or
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opportunity to gain experience towards achieving research independence. About you The ideal candidate will hold a PhD in experimental (quantum) physics or a closely allied discipline. Possess strong skills in