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This project is technical in nature and would suit a candidate with a background and interest in #Java programming, health informatics or health data (or a combination thereof). The primary aim
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This project will explore the use of Mixed-Reality (MR) headset technology to support people in performing maintenance tasks in complex environments, where the nature of the work involves close
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knowledge program analysis, fuzzing, software testing, natural language processing
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Many machine learning (ML) approaches have been applied to biomedical data but without substantial applications due to the poor interpretability of models. Although ML approaches have shown promising results in building prediction models, they are typically data-centric, lack context, and work...
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classification'', Computer Journal, Vol 11, No 2, August 1968, pp 185-194 Wallace, C.S. and D.L. Dowe (1999a). Minimum Message Length and Kolmogorov Complexity, Computer Journal (special issue on Kolmogorov
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an electrical and computer systems engineering degree in the Faculty of Engineering. Total scholarship value $20,000 Number offered One at any time See details Farrell Raharjo Clive Weeks Community Leadership
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Skip to main content Main Menu - Primary Home Projects Supervisors Expression of Interest Contact Faithful and Salient Multimodal Data-to-Text Generation Primary supervisor Teresa Wang Co-supervisors Yuan-Fang Li Derry Wijaya Mohammed Eunus Ali Research area Vision and Language While large...
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We live and work in a world of complex relationships between data, systems, knowledge, people, documents, biology, software, society, politics, commerce and so on. We can model these relationships
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their potential at Monash University. The scholarship program amplifies diversity in STEM through empowering scholarship recipients to achieve academic success. Total scholarship value $6000 Number offered 10 See
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for Earth" grant by Microsoft, one of only 6 projects in Australia to receive this recognition. The new project will build original frameworks for future applications of Machine Learning and Computer Vision