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at developing methodological contributions at the intersection of computer vision, multimodal learning, predictive world models, embodied AI, and human-robot interaction. The candidate will work towards models
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from Monash Graduate Research Office as a one-off travel grant The Opportunity As part of the CSIRO Industry PhD scholarship program , this is an unprecedented opportunity for an outstanding data science
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student enrolled in Bachelor of Biomedical Science Industry Honours (M3702), Bachelor of Science Industry Honours (S3701). WAM 70+ Benefits $10,000 paid in 2 equal instalments, for one year only. Number
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Large language models increasingly adapt using external feedback to alter inference-time behaviour, persistent state or model parameters. However, the signals that drive these changes may be noisy, biased, incomplete, delayed, correlated with the model’s own errors, or progressively underused...
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hybrid cloud environments. You will drive the modernisation of Monash’s Linux capability through automation, Infrastructure as Code, observability, platform engineering and AI-enabled operations, while
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discover them The Opportunity Join the School of Physics and Astronomy within the Faculty of Science as a Research Fellow and contribute to internationally recognised research in experimental particle
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First Class Honours or a Master's degree in a relevant discipline. Depending on the project, suitable backgrounds may include: Engineering Computer Science Artificial Intelligence GIS and Spatial Science
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Migration Analyst will join the Student Management System Transformation (SMST) Program, supporting the Data Migration Lead in delivering an end to end data migration solution to enable migration of data from
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and Evidence-to-Decision frameworks · Use and evaluation of digital guideline platforms (MAGICapp) · Implementation science and knowledge translation in rheumatology
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of foundation models in natural language processing and computer vision, this project seeks to develop general-purpose graph foundation models capable of learning transferable representations from large-scale