664 systems-science-"https:"-"https:"-"https:"-"https:" positions at Monash University in Australia
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such as energy, water, food and waste. This PhD forms part of the Australian Research Council Discovery ‘Project Empowering households in resource-efficient sustainability transitions’, which is a
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The primary objective of this project is to enhance Large Language Models (LLMs) by incorporating software knowledge documentation. Our approach involves utilizing existing LLMs and refining them
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Conventional x-ray imaging is firmly established as an invaluable tool in medicine, security, research and manufacturing. However, conventional methods extract only a fraction of the sample
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Advisory System, or data from other implantable or wearable devices. This involves consideration of both feature-based machine learning or data science approaches and neural mass parameter estimation
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This PhD project is funded by a successful ARC Discovery Project grant: "Improving human reasoning with causal Bayesian networks: a user-centric, multimodal, interactive approach" and the successful
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Faculty of IT International Merit Scholarship Sir John Monash Fee Scholarship This scholarship is for international students committed to studying at the Faculty of Information Technology at Monash
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This Ph.D. project aims to combine causal analysis with deep learning for mental health support. As deep learning is vulnerable to spurious correlations, novel causal discovery and inference methods
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& Research Access Support: support with accessing research materials or sites, such as scanning, photocopying, retrieving physical texts, or navigating library systems. Accessible Technology, Materials
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Department of Economics Honours Merit Scholarship Sir John Monash Scholarship for Excellence This scholarship is awarded to high achieving students who enter into the Bachelor of Commerce (Honours
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promising results in building prediction models, they are typically data-centric, lack context, and work best for specific feature types. Interpretability is the ability of an ML model to identify the causal