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the brain. This wouldn't be a typical machine learning PhD, as many aspects can only be examined on a philosophical and theoretical level. There may be scope to implement aspects in the ideas you develop
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We are seeking a motivated PhD candidate to work on unsupervised music emotion tagging within the broader field of affective computing. The project aims to develop reproducible machine learning
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optimisation Large-scale data processing Intelligent and educational analytics Rather than replacing classical systems, the project will develop hybrid architectures where quantum components assist specific
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the evolution of massive binary stars into compact binaries as sources of gravitational-waves and astrophysical inference on gravitational-wave observations. My research group on massive binary evolution -- also
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to access leadership and community engagement opportunities and to support the development of emerging engineering leaders to encourage these talented individuals to enter the mining industry upon completion
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existing insights and resources developed by industry partner Silverchain, the student will co-design low-fidelity prototypes and progressively develop a minimum viable platform that includes scenario-based
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Minimum Message Length (MML) is an elegant information-theoretic framework for statistical inference and model selection developed by Chris Wallace and colleagues. The fundamental insight of MML is
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or academia in an under-developed domain. You will, therefore, need to have an honours degree or Masters in psychology or a related social science field (e.g., business studies, criminology, sociology
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model with each SNP independently, perhaps adjusting for other covariates such as age and sex. This project will focus on developing and applying novel machine learning and AI methods to improve
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, and their decisions can be confusing due to brittleness, there is a critical need to understand their behaviour, analyse the (potential) failures of the models (or the data used to train them), debug