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Machine Learning for Image Classification. Eligibility You must: We would like you to have: sound knowledge of machine learning, computer vision and image processing strong programming skills. How to apply
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Conventional x-ray imaging is firmly established as an invaluable tool in medicine, security, research and manufacturing. However, conventional methods extract only a fraction of the sample
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will receive a Research Living Allowance, at current value of $37,145AUD per annum 2026 full-time rate (tax-free stipend), indexed plus allowances as per RTP stipend scholarship conditions at: https
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experience. Knowledge of quantitative and qualitative research methods highly desirable. Proficiency in a language other than English is highly desirable. Evidence of journal or conference publications
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environmental economics. RESEARCH ENVIRONMENT This project will be under the primary supervision of Dr Brooke Williams, you will join the new Biodiversity, Forest Restoration, and Ecology (BIOSFERE) Lab https
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the development of numerical methods for astorphysical fluid dynamics and radiation transport. Projects may employ a range of approaches from analytic modelling and numerical calculations on desktop
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practices in professional physics and students' engagement in these practices The role of agency in students learning physics practice A mixed-method, longitudinal study on factors related to retention in
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the optical-to-radio wavelength range, from major surveys and space telescopes (e.g: Gaia, SDSS, JWST, Hubble, Roman, Rubin-LSST). These are analysed using advanced machine learning and data-driven methods. My
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on supporting the social and psychological processes involved in behaviour change. The project uses mixed methods, including focus groups and surveys with people under the supervision of the Department
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better supported to understand, enact, and sustain physical literacy–focused practices in diverse sport and education contexts. Using a mixed-methods, co-design research approach, the study will be