299 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"NOVA.id" positions at Monash University
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. This work combines computational modelling and simulation with biological experiments that are analysed using cutting-edge computer vision techniques. We collaborate closely with Macquarie University where
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known human reasoning difficulties and fallacies. It will also investigate how to reduce human cognitive load by prioritising the most useful information for the user. Expected outcomes include novel AI
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combination of multi-wavelength observational data with sophisticated simulations. I am a member of various collaborations, including Australia's OzGrav Centre of Excellence for Gravitational-wave Discovery
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reconstruction and data analysis. The PhD students will be working at Monash Biomedical Imaging and Faculty of Information Technology, Monash University. Monash Biomedical Imaging is one of the most advanced
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explore unconventional ideas, develop computer algorithms for data analysis, create new experimental approaches, and apply the technique in areas like biomedicine, materials science, and geology. My group
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paradigms rely on a fragile "closed-world" assumption: that the unlabeled pool perfectly reflects the distribution of the labelled seed set. In real-world deployments, this is rarely true. Data streams
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area Software Engineering The objective of this project is to design automated approach to detect bugs in various software, e.g., compilers, data libraries and so on. The project may involve LLMs
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and questionnaires and manage data collection and analysis. It will also ensure REDCap data integrity, prepare protocol-aligned results and support reporting, manuscripts, presentations and related
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The proliferation of misinformation and disinformation on online platforms has become a critical societal issue. The rapid spread of false information poses significant threats to public discourse
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weighted sum of the risks from tens to millions of independent disease-associated SNPs from across the genome. The conventional, or gold-standard, approach to analysis of GWAS data is to fit a regression