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PhD Scholarship Develop multimodal machine learning models to predict glioblastoma treatment outcomes using imaging and clinical data. Work with real-world data from John Hunter Hospital in a
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materials systems at the molecular level with machine learning. The PhD Student will work with tumour sections to develop multiple instance learning and weak supervision / spatial transcriptomics models
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Machine learning has recently made significant progress for medical imaging applications including image segmentation, enhancement, and reconstruction. Funded as an Australian Research Council
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" "Machine-learning-based imaging processing" webpage For further details or alternative opportunities, please contact: haoran.ren@monash.edu.
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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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they bond in materials, but also develop transferable skills in scientific computing, data analysis and visualisation. "Machine learning for atomic-scale structure determination in thick nanostructures" (with
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factors involved in the onset and progression of dementia. Advanced computational methods, including bioinformatics pipelines and machine learning, will be employed to uncover putative biomarkers and
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Environmental Engineering Mechanical and Aerospace Engineering Electrical and Computer Systems Engineering Chemical and Biological Engineering Materials Science and Engineering About the Role We are seeking
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, and machine learning/artificial intelligence. This project focuses on the development of novel theoretical frameworks alongside cutting-edge computational techniques for large-scale optimisation
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. Why Your Role Matters: The School of Humanities & Social Sciences provides an understanding of how we navigate the world, what we can learn from our past and how we can make a difference going forward