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PhD Opportunity - Indigenous (Energy) Job No.: 685291 Faculty / Portfolio: Faculty of Information Technology Location: Caulfield or Clayton campuses Duration: 3.5-year fixed-term appointment
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materials systems at the molecular level with machine learning. The PhD Student will undertake a study analysing mass spectral imaging data streams in real time using machine learning workflows. A pathway for
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the world. Ideal applicants will have a solid background in AI, machine learning, control theory or quantitative finance. Applicants with advanced programming skills (Python/C++); and a desire to publish in
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-team and contribute to a clinical trial research project of national significance for youth mental health. The project applies modern data science methods to build explainable and integrated machine
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data science methods to build explainable and integrated machine learning models that can be utilised by health services to make real-time, data-informed clinical decisions in youth mental health care
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deep learning. The purpose of this scholarship is to support a PhD student to contribute to the advancement of infrastructure monitoring technologies with strong industry collaboration. Student type
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interaction and human motion analysis Prior knowledge of machine learning/deep learning applied to motion analysis (e.g., relevant courses and research experience) would be an advantage IELTS score of 6.5
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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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external enrolment procedures. Selection criteria Demonstrated experience in programming and system development. Expertise in Python programming and data analysis. Experience developing Machine Learning
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group of PhD researchers who will tackle the most pressing questions in Machine Learning while ensuring AI serves humanity responsibly. You'll work within one of our specialised research themes, each