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Applied mathematics, fluid mechanics, high-performance computer simulations. Full time, fixed term position (3 years) at Hawthorn campus $34,700 per annum (2025 rate) About the Scholarship Higher
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PhD Scholarship in Digital Mapping of Homemade & DIY Cultural Economies in First Nations Communities
for research that benefits Indigenous communities – in a relevant disciplinary area, including Human-Computer Interaction, Media Studies, Digital Cultures, Digital Sociology and Digital Humanities
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challenging for clinicians and pregnant women. Digital health records, advances in big data, machine learning and artificial intelligence methodologies, and novel data visualisation capabilities have opened up
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) and computer simulation (FEA) Experience in material characterisation and experimental testings Knowledge in impact dynamics Passionate and have interest in pursuing PhD degree. Experience in research
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of generative AI. Essential Skills and Experience A background in a relevant field such as behavioural science, cognitive science, data science, psychology, human-computer interaction, law, or a related
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well as children. To identify the specific mechanisms through which multisensory stimulation enhances motor learning, working memory, and auditory selective attention. To compare the effectiveness of different
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courses. Browse all courses Take your development further with advanced learning and award pathways. Pathways to Politics for Women Public Sector Management Enterprise Leadership For organisations Achieve
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. • Proficient computer skills, including competence in the use of MS Office and other software packages, especially word processing, database and spreadsheet skills. About Swinburne University of Technology
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world, and with world-class photonic facilities at Monash. "Quantum nanophotonic chip" "Multimode imaging through ultrathin meta-optics" "Advancing optical imaging with flat optics" "Machine-learning
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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