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-offs between the modularity (henceforth interpretability) and the efficiency in existing end-to-end modular autonomous driving models. In this PhD project, student is expected to conduct research in
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catastrophically so. This PhD will develop technologies for addressing this serious problem, building upon our groundbreaking research into the problem. Required knowledge A solid grounding in machine learning
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Time series are an ever growing form of data, generated by numerous types of sensors and automated processes. However, machine learning and deep learning methods for analysing time series are much
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I am seeking PhD candidates interested in working on designing Learning Analytics innovations to study classroom proxemics by analysing and visualising indoor positioning data (along with other
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these challenges, calling for the development of responsible AI systems that are transparent, trustworthy, and aligned with human values in educational contexts. This PhD project aims to design, develop, and
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Species’ distributions are shifting in response to global climate change and other human pressures. Accurate methods to monitor and predict distribution shifts are urgently needed to manage
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). The reason for this is that the candidate will need to be trained in theories about humans and experimental methods. Meet H1E requirements for Monash FIT PhD entry.
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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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Short description The PhD project is focused on recommended design and engineering principles of totally renewable microgrids with the ambition to outperform traditional networks reliability
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of vulnerability. Arguably, cybersecurity scholars need to learn much more about the methods criminals employ to trick victims out of money. This PhD scholarship will extend upon Prof Whitty's work in this field