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Doctor of Philosophy (PhD) in Machine Learning for In Situ Materials Characterisation Job No.: 698995 Location: Clayton campus Employment Type: Full-time Graduate Research Degree: 3291 - Doctor
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PhD Scholarship Develop AI and machine learning models to guide real-time, personalised treatment of paediatric brain cancer using multiomics and clinical data, within the internationally
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PhD Scholarship in Multimodal Federated Learning and Medical Image Analysis Job No.: 695949 Location: Clayton campus Employment Type: Full-time Duration: 3-year and 3-month fixed-term appointment
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PhD Scholarship Opportunity - Processing intelligence for green metals using in situ X-ray characterisation and machine learning Job No.: 693787 Location: Clayton campus Employment Type: Full-time
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. • be located at the agreed project location(s) and, if required, comply with the university’s external enrolment procedures. Selection criteria Skillset: Proficient in Python, machine learning, and
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Fluor Mining and Metals (Virta Inc.) throughout the term of the project, with opportunities to travel to further develop models and acquire validation data. Expected Outcomes The expected outcomes
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. The research combines robotics, computer vision, artificial intelligence, machine learning, control systems, and medical robotics to solve one of the most challenging problems in modern automation. Project
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motivation Testing whether the system performs equitably across cultural and language groups Training spans intervention design, trial methodology, human-computer interaction, and applied machine learning
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learning at one of the world’s top 50 universities Take your career in exciting, rewarding directions A fully funded PhD scholarship is available in the group of Dr Wael Awad within Prof. Jamie Rossjohn’s
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, segmentation, anomaly detection and learning in the context of non-stationary distributions. The candidate will also be connected to the Faculty of Information Technology. The Temporal Analytics Lab, directed by