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Australasia. More than 9,000 students study across our ten schools and departments, learning from internationally recognised educators and researchers. Our staff and students can connect with our flagship
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, Educational Technology, Learning Sciences, Human-Computer Interaction, or a related discipline. Strong interest in research relating to Generative AI, AI literacy, digital learning, workplace learning, or human
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interacts with the human body—making it a key factor in both product performance and consumer satisfaction. You will also apply statistical and machine-learning tools to explore how cotton fiber properties
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research infrastructure. Apply advanced statistical, machine learning and data engineering methodologies to large-scale, longitudinal datasets, contributing to innovative melanoma and skin cancer research
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: To independently undertake research in machine learning. To produce research reports and/or publications as required by the funding body or for dissemination to the wider academic community. To provide guidance and
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machine-learning, predictive-modelling or multivariate methods to behavioural and/or EEG data. Proficiency in R, MATLAB and Python. What we can offer In return we offer a generous pension, relocation
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machine learning and AI acceleration. Perform performance, power, and area (PPA) analysis of processor and accelerator designs. Publish research findings in top-tier conferences and journals and contribute
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Responsibilities: To independently undertake research in machine learning. To produce research reports and/or publications as required by the funding body or for dissemination to the wider academic community
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, primitives for quantum machine learning, and advanced aspects of learning theory. The work is both theoretical, i.e., formulating and proving theorems, and numerical, i.e., converting algorithms into code and
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ideal for a researcher with a passion for solving complex problems at the intersection of wireless communications, edge computing, and machine learning, and who is eager to translate theoretical insights