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implement algorithms that efficiently analyse extreme value statistics in nonstationary dynamical systems arising from idealised models or data. Collaborative publications in leading international
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traditional and advanced optimization techniques, including analytical models, simulation-based approaches, and data-driven algorithms. The research also considers practical constraints such as cost, process
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on developing algorithms to analyse optical signals extracted from video images to obtain vital signs with high accuracy. Key responsibilities include: Robust feature extraction from biomedical signals
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the construction of PRS and enhance disease prediction. Students will gain experience in: Statistical genetics and GWAS methodology Machine learning approaches for high-dimensional data Algorithm development and
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new algorithms to analyse compliance of CER according to relevant Australian standards (AS 4777.2020.2, CSIP-AUS, IEEE). Creating new algorithms to analyse curtailment of CER according to relevant
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formative assessment and personalised feedback while ensuring fairness, accountability, and transparency. The research will explore a combination of algorithmic design, human–AI interaction, and empirical
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estimation methods for deep neural networks. A principled Bayesian framework for multimodal uncertainty modeling. Robust learning algorithms under missing modalities and distribution shifts. New uncertainty
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practice of imaging, cardiac mapping and targeted radiation therapy Create, develop and experimentally and clinically implement mechanistic and AI based algorithms Support the acquisition and analysis
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produce software implementations of the algorithms developed in this project. About you The University values courage and creativity; openness and engagement; inclusion and diversity; and respect and
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | about 1 month ago
and PEWER Research Fellow_561790.pdf The position will provide opportunities to Conduct cutting edge research in AI and algorithms. Opportunity to supervise research students and work as part of a