460 engineering-computation-"https:"-"https:"-"https:"-"https:"-"https:"-"NOVA.id" positions at Monash University
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per year: one in the Humanities and Social Sciences (HASS) disciplines. one in the Science, Technology, Engineering and Mathematics (STEM) disciplines. Selection criteria Monash scholarships are highly
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the Humanities and Social Sciences (HASS) disciplines. one in the Science, Technology, Engineering and Mathematics (STEM) disciplines. Selection criteria Monash scholarships are highly competitive and are awarded
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to work closely with other leading academics at Monash University, including Professor Carol Propper , A/Prof Terrence Cheng and Dr Danusha Jayawardana . As a candidate in the CHE Integrated PhD Program
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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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Project Description Recent advances in mixed reality (MR) technology, which seamlessly blend the physical environment with computer-generated content around the user, have reduced the barriers
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inference. PhD Program The project is based in the Centre for Health Economics, a large and active economics research group within the Monash Business School in Melbourne, Australia. As a candidate in the CHE
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This project explores the development of digital tools that measure the carbon footprint and nutritional impact of meals to support sustainable eating. It aims to integrate environmental and nutritional data into a user-friendly platform, enabling consumers, restaurants, and policymakers to make...
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Emeritus Professor Codner Scholarship Achieving Potential Support Scholarship The Emeritus Professor Codner Scholarship has been established to provide support for commencing Faculty of Engineering
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of Music (and Double Degrees) with a specialisation in any stream (Classical Music Performance, Composition and Music Technology, Jazz and Improvisation Performance, Popular Music) in the Sir Zelman Cowen
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Machine learning has recently made significant progress for medical imaging applications including image segmentation, enhancement, and reconstruction. Funded as an Australian Research Council Discovery Project, this research aims to develop highly novel physics-informed deep learning methods...