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. The project aims to develop cutting-edge machine learning and statistical risk prediction techniques to predict each short-term, long-term and cost outcomes, which include but are not limited to
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. The project aims to develop cutting-edge machine learning and statistical risk prediction techniques to predict each short-term, long-term and cost outcomes, which include but are not limited to
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, testing, and operation. Required knowledge deep learning, natural language processing, software testing Learn more about minimum entry requirements .
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, testing, and operation. Required knowledge deep learning, natural language processing, software testing Learn more about minimum entry requirements .
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-reviewed publications in Data61’s target conference venues, open-source AI datasets, training scripts, and trained models. Required knowledge Generative AI NLP skills System security Software testing
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-reviewed publications in Data61’s target conference venues, open-source AI datasets, training scripts, and trained models. Required knowledge Generative AI NLP skills System security Software testing
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Primary supervisor Mohammad Goudarzi Research area Software Systems and Cybersecurity In SmartScaleSys (S3), we aim to design and build resource management solutions to learn from usage patterns
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affected by AMR pathogens. This will be achieved by integrating cutting-edge techniques in bacterial genomics, including both short-(Illumina) and long-read sequencing (Oxford Nanopore), data mining of
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personalise therapy of patients at-risk or affected by AMR pathogens. This will be achieved by integrating cutting-edge techniques in bacterial genomics, including both short- (Illumina) and long-read
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personalise therapy of patients at-risk or affected by AMR pathogens. This will be achieved by integrating cutting-edge techniques in bacterial genomics, including both short- (Illumina) and long-read