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funded project aimed at enhancing medical diagnostics through the application of machine learning and artificial intelligence. In this capacity, you will lead the development of algorithms to improve
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candidates must hold (or close to completing) a PhD in a relevant subject. Knowledge and experience in computer vision is required. Experience of efficient ML techniques, edge AI hardware platforms, low-power
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, alongside a collaborative approach. Prior experience in computational modelling, the application of machine learning, and development of precise optical experiments and instrumentation will be advantageous
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research (machine learning, multi-agent systems, causal AI, optimisation), along with participation in a range of multidisciplinary research projects that will not only include developing AI systems for good
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Machine Learning, Statistics, or a related field, who have in-depth knowledge in and demonstrable experience with: Recent deep learning techniques, including, e.g., diffusion models and attentional models
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with a Ph.D. (either awarded or nearing completion) or equivalent professional qualification and experience in Machine Learning, Statistics, or a related field, who have in-depth knowledge in and
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image processing, biometrics, security, machine learning or a related discipline, and the ability to write for publications, present research proposals and results to non-scientific audiences
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bioinformatics, epidemiology, systems biology, large-scale ‘Omics data analysis, human centric artificial intelligence, machine learning or large data management. We are seeking candidates whose expertise spans
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welcome applications from scholars working to tackle largescale, globally relevant problems, using advanced computational methods (e.g. big data/machine learning/artificial intelligence/modelling/remote
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. We welcome applications from individuals who wish to innovate research and teaching in mental health with specific expertise on machine learning and artificial intelligence methods. You will hold a