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is pivotal in ensuring the reliability, scalability, and maintainability of our physical data centre environment, which supports both advanced research computing and critical enterprise services. You
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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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of Computer Science in Data Science (Honours) Anban Raj Thank you will never suffice to express my gratitude to the Ng Family for believing in my potential and enabling me to access a world-class education. I will
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Senior Advisor, Quality and Projects Job No.: 680000 Location: Clayton campus Employment Type: Full-time Duration: Continuing appointment Remuneration: $140,157 - $148,769 pa HEW Level 09 (plus 17% employer superannuation) Amplify your impact at a world top 50 University Join our inclusive,...
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The ARC SRIEAS Securing Antarctica’s Environmental Future (SAEF) program is a leading international research initiative from the Faculty of Science focused on forecasting and addressing environmental change
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to advance computer skills are desirable, but not essential. A valid driver’s license and willingness to drive to general practice clinics, patient homes and other care settings, will be required. This is
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We are living in the era of the 4th industrial revolution through the use of cyber physical systems. Data Science has revolutionised the way we do things, including our practice in healthcare
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David Shugg Professionalism Scholarship Industry Leaders Scholarship This Scholarship is to honour the important role that David Shugg played in the professionalism of paramedics. Throughout David’s career, he advanced and embedded professionalism in paramedic training and education in the...
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discover them The Opportunity An exciting opportunity exists to join the Department of Management within the Faculty of Business and Economics as an Associate Professor of Geopolitics and International
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., Pan, S., Aggarwal, C., & Salehi, M. (2022). Deep learning for time series anomaly detection: A survey. ACM Computing Surveys.