616 embedded-system-"https:"-"https:"-"https:"-"https:"-"Leeds-Beckett-University" positions at Monash University
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Synthetic data generation has drawn growing attention due to the lack of training data in many application domains. It is useful for privacy-concerned applications, e.g. digital health applications
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-making and ensures the sustainable operation of teaching, research and service delivery activities. The position is responsible for providing financial support and guidance to managers and staff across
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requirements. The role contributes to the development of personalised interventions informed by both clinical expertise and lived experience. The position is responsible for supporting the coordination and
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integral to maintaining assessment integrity while contributing to efficient, error-free operations across the assessment lifecycle. This position will be responsible for delivering expert quality assurance
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systems. The fast growth, practical achievements and the overall success of modern approaches to AI guarantees that machine learning AI approaches will prevail as a generic computing paradigm, and will find
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of Social Sciences is seeking a Level B research-only candidate to undertake independent and collaborative research within a multidisciplinary project, Empowering households in resource-efficient
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, attention to detail, and the ability to manage marking responsibilities within set deadlines. The capacity to work both independently and collaboratively as part of a teaching team is essential. This is an
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analysis, contextual analysis, audio feature extraction, and machine learning models to identify and assess potentially dangerous content. Similarly, computer vision models are implemented to analyse images
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responsible for delivering high-quality technical, operational, and safety support across multiple laboratory facilities, including SAMPL and the MiLabs. The role applies advanced technical knowledge to support
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This Ph.D. project aims to combine causal analysis with deep learning for mental health support. As deep learning is vulnerable to spurious correlations, novel causal discovery and inference methods