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? Moving from RISE’s initial 12 pilot settlements to nationwide implementation requires robust, adaptable engineering solutions. Building on monitoring and performance data from existing sites, this research
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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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immunocompromised populations; and providing evidence to inform national health policy. Ideal For: Candidates with an interest or background in biostatistics, epidemiology, data science, or public health registry
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for infrastructure platforms in minerals-to-green metals transformation. It will suit a candidate interested in combining experimental materials science, advanced characterisation, and data-driven modelling to develop
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(or delegate); and Relevant disciplines include health economics, labour economics, economics, econometrics, and other quantitative fields such as data science, mathematical statistics, health policy, public
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infrastructure, public safety and smart environments. The successful candidate will be supervised by Dr Deval Mehta within the Department of Data Science & AI, Faculty of Information Technology, Monash University
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Indo-Pacific region. The MAI is a premier hub for AI and data science research in the Asia-Pacific, focused on advancing AI for real-world impact. It brings together experts from computer science
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Bachelor's degree with Honours (First Class or equivalent) or a Master's degree in a relevant discipline. • A strong academic record in fields such as chemical engineering, materials science, chemistry
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electromagnetic signatures, primarily focussed on linking the data from these exciting experiments with our theoretical understanding of gravity and the most extreme regions of the Universe. I am a member of the
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, which are some of the most numerous stars in the Universe. "Weighing stars using stellar vibrations: Asteroseismic masses of Red Giant Stars using space telescope data" "Using optical telescope