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for computational analysis. This learning analytics project will be conducted in the context of simulation-based healthcare education, and it will support the development of effective strategies to improve teamwork
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application performance. The role will maintain a structured GitHub repository, establish automated deployment workflows, develop user and developer documentation and deliver technical handover, while
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focus on foundation models, medical image analysis, and multimodal healthcare data integration. In this role, you will: Develop novel federated AI methodologies, foundation model adaptation techniques
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or a related higher education environment, together with recent experience coordinating projects, admissions activities or operational initiatives. You will have strong analytical, organisational and
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of work in line with the broader portfolio plan and Impact 2030, including delivering communications and content in line with the research and enterprise agenda. Further, you will develop
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Histology Technical Officer Job No.: 695268 Location: Clayton campus, Monash Health Translational Precinct Node and Alfred Medical Research and Education Precinct Node Employment Type: Full-time
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𝐢𝐧𝐟𝐫𝐚𝐬𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞. This research addresses a critical challenge in modern AI: how to train increasingly large models in a more scalable, accessible, and sustainable way. As AI systems continue to grow, centralised
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copyright - Privacy , Monash University CRICOS Provider Number: 00008C, Monash College CRICOS Provider Number: 01857J. Monash University is a registered higher education provider under the TEQSA Act 2011. We
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education and are committed to helping more care leavers access further education. The Achieving Potential Care Leaver Scholarships are provided to commencing students whose educational achievements may have
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discovery. While deep generative models have shown promise in proposing novel molecular structures, they typically require massive, cleanly labelled datasets to train effectively. In practice, acquiring high