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Engineering International High Achievers Scholarship Sir John Monash Fee Scholarship The Engineering International High Achievers Scholarship is introduced to recognise high achieving international
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computational methods for modelling social dilemmas that can account for real-world complexity in agents’ behaviour. We will build on novel computational techniques to produce realistic enough models that can be
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Skip to main content Main Menu - Primary Home Projects Supervisors Expression of Interest Contact Computational drug discovery Primary supervisor Geoff Webb Research area Data Science and Artificial
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Engineering Indigenous Excellence Scholarship Achieving Potential Scholarship for Excellence The Engineering Indigenous Excellence Scholarship has been introduced to support Indigenous students
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of Machine Learning (ML) models across large-scale distributed systems. Leveraging advanced AI and distributed computing strategies, this project focuses on deploying ML models on real-world distributed
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Master of Engineering pathway program. Up to 10 scholarships valued at up to $30,000 are available each year. Applications No application required Total scholarship value Up to $30,000 Number offered Ten
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This project focuses on brain network mechanisms underlying anaesthetic-induced loss of consciousness through the application of simultaneous EEG/MEG and neural inference and network analysis methods. In this work we study the effects putative NMDA antagonists xenon, a potent anaesthetic, and...
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Malaysia, forming part of Monash University’s Faculty of Business and Economics. Our structure includes seven discipline-based departments and a wide range of research centres exploring behavioural economics
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Computational simulations are now widely employed to study the behaviour of social systems, examples being market behaviours, and social media population behaviours. These methods rely heavily
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Automated Program Repair (APR) is the grand challenge in software engineering research. Many APR methods have shown promising results in fixing bugs with minimal, or even no human intervention