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predictive capability for post-TAVR outcomes against traditional metrics. iii) Incorporate the AI-based frailty evaluation into surgical risk scores for a comprehensive risk prediction. iv) Examine the model's
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to apply for a research degree . In your EOI, copy the link to this scholarship website into Question 2 of the financial details section. About the scholarship The candidate will be supervised by Prof Cheng
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degree . In your EOI, copy the link to this scholarship website into Question 2 of the Financial details section. About the scholarship The candidate will be supervised by Prof Cheng Yan and an expert team
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challenge is to combine our best theories of fundamental physics to model what happens at ultra-short distances. This project will generate new knowledge at this interface by using a novel approach inspired
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(april.kartikasari@rmit.edu.au ). A copy of electronic academic transcripts A CV that includes any publications/awards and the contact details of two referees. To apply, please submit the following documents to Prof
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@rmit.edu.au A cover letter (research statement) A copy of electronic academic transcripts A CV that includes any publications/awards and the contact details of two referees Thesis or research reports
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observational research (e.g., simulations) and/or lab or field experiments Experience with the analysis (e.g., sequential analysis, multilevel modelling) and interpretation (e.g., conference presentation
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at the intersection of user modelling, multi-agent systems, simulations and modelling, reinforcement and deep learning, evaluation and responsible AI. We understand it is unlikely someone will have a background in all
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at the intersection of user modelling, recommender and information retrieval, simulations and modelling, evaluation and responsible AI, focused on media and cultural curation applications. We understand it is unlikely
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to trick AI-based models, pay little attention to fake-normal data traffic generated by Generative Adversarial Networks (GAN). This PhD research will address a major vulnerability in AI based smart grids by