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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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Remuneration: The successful applicant will receive a tax-free stipend, at the current value of $35,013 per annum 2024 full-time rate, as per the Monash Research Training Program (RTP) Stipend . Monash
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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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of Medical Science and Doctor of Medicine Thomas I very much enjoyed my placements in Sale and Bairnsdale and felt welcomed by the East Gippsland community. I am very grateful to receive this scholarship which
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In recent years, the rise in cybercrimes has significantly increased the vulnerability of the open internet to various threats and cyber-attacks. Among these, phishing stands out as one of the most perilous crimes worldwide. In a phishing attack, perpetrators create fraudulent websites that...
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This project focuses on developing algorithms capable of automatically identifying and categorizing mobile ringtones. This involves leveraging machine learning techniques to analyze audio signals from mobile devices and classify them into different categories or types of ringtones. The...
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aims to explore who takes physics and astrophysics major units, why they pursue them, and what obstacles they may face. There are a number of research questions under this umbrella. Computational
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Bachelor of Occupational Therapy (Honours) The Betty Amsden program helped me gain clarity about my career pathway and increase my confidence. I think these were strong contributing factors to excelling in
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that occurs within these biological neural networks, so that these networks can be leveraged for AI applications. In addition, you will develop mathematical and computational neuroscience models
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. Leveraging techniques such as federated learning, differential privacy, and secure multiparty computation, the goal is to enable collaborative ML tasks without compromising the privacy of individual data