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computer science, information technology, artificial intelligence, machine learning, software engineering, computer/electrical engineering, or a closely related discipline. This PhD project is part of a
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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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limited to ordinary machine-learning evaluation where models are tested only on clean datasets. It is also not just a general cybersecurity project disconnected from healthcare. The security problems
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We are seeking a motivated PhD candidate to work on unsupervised music emotion tagging within the broader field of affective computing. The project aims to develop reproducible machine learning
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This Masters or PhD project aims to explain the uncertainty of Machine Learning (ML) predictions. To this effect, we must quantify uncertainty, devise algorithms that explain ML predictions and
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PatchSentinel-X: Transformer-Based Security Patch Intelligence for Vulnerability Lifecycle Assurance
prototype A prototype that can support secure code review by producing patch trust scores and review recommendations. Required knowledge Essential Python programming, Machine learning fundamentals, Deep
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. Required knowledge Strong background in machine/deep learning, computer vision, or applied statistics. Solid programming skills in Python and experience with deep learning frameworks (e.g., PyTorch
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the brain. This wouldn't be a typical machine learning PhD, as many aspects can only be examined on a philosophical and theoretical level. There may be scope to implement aspects in the ideas you develop
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PhD Studentship Description: The studentship will be based at Monash University Monash Medical AI Group led by Associate Professor Zongyuan Ge. The successful candidate will join a multi
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is not about building another normal intrusion detection system. It is also not about simply applying machine learning to classify network traffic as normal or malicious. The project is not focused