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tissues or reveal micro- or nano-structural features, like the small air sacs in lungs. To overcome these limitations, alternative X-ray imaging methods have been developed: X-ray phase-contrast and dark
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analysis, contextual analysis, audio feature extraction, and machine learning models to identify and assess potentially dangerous content. Similarly, computer vision models are implemented to analyse images
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technologies will affect them. It is our anticipation that the work will commence with, in parallel, the survey for collecting the data and a comparison of machine learning methods on artificial pseudo-randomly
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-quality research publications in econometrics or related fields. You will possess the ability to solve complex statistical problems, show advanced computer literacy with proficiency in relevant software
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to work independently and collaboratively. Advanced planning, time management, and written communication skills are essential, along with proven computer literacy and proficiency in relevant software and
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Factors, patient safety, healthcare quality and clinical research or systems improvement; Demonstrated skills in qualitative or mixed methods research, data collection and analysis; and Knowledge of Human
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people who discover them The Opportunity The Department of Electrical and Computer Systems Engineering is seeking applications for a Level A Research Fellow to contribute to a high-impact research project
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The Level A Research Fellow will contribute to the research efforts of the Department of Electrical and Computer Systems Engineering, with a specific focus on advancing a cutting-edge research program in
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content creation software, assessment designs, evaluation methods, multimedia learning theory, universal design principles, and project management. For candidates that demonstrate a quality track record of
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quantitative, qualitative, or mixed research methods. About Monash University At Monash , work feels different. There’s a sense of belonging, from contributing to something groundbreaking – a place where great