107 data-"https:"-"https:"-"https:"-"Computer-Vision-Center" PhD positions at Monash University
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. Novel Adversarial Machine Learning algorithms for structured data will be proposed. The algorithms will be further extended to graph-structured data. Applications of AML will also be investigated to
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. Novel Adversarial Machine Learning algorithms for structured data will be proposed. The algorithms will be further extended to graph-structured data. Applications of AML will also be investigated to
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machine/deep learning, computer vision, or applied statistics. Solid programming skills in Python and experience with deep learning frameworks (e.g., PyTorch or TensorFlow) Project funding Other Funding
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[Malaysia Campus- VPSSP] An AI-Informed Planetary Health Framework for Equitable AMR Risk Mitigation
ensure local relevance. Required knowledge Artificial Intelligence; Machine Learning; Computer Vision; Bioinformatics; Biomedical Engineering; Neuroscience; Genomics; Medical Physics; Data Science
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Spectral Encoding. Develop advanced neural architectures (e.g., adapted Vision Transformers or 1D sequence models) capable of fusing multiple distinct analytical "views" (e.g., combining MS2 and NMR data
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. The project will advanced state of the art AI for NLP or vision or both and embed self-awareness modules within these systems. This will likely involve a combination of the standard methods in these
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. The project will advanced state of the art AI for NLP or vision or both and embed self-awareness modules within these systems. This will likely involve a combination of the standard methods in these
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question will be developed with the student and could focus on publishing, peer review, research funding, scientific careers, collaboration, or the norms governing AI use. Projects may also use data from
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sequencing (Oxford Nanopore), data mining of electronic medical records and use of machine learning to predict several outcomes. Among the approaches used will be the Bayesian information-theoretic
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sequencing (Oxford Nanopore), data mining of electronic medical records and use of machine learning to predict several outcomes. Among the approaches used will be the Bayesian information-theoretic