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PhD Opportunity This project will involve epidemiologic analysis of FluTracking and published data to explore how self-testing and vaccination behaviour have evolved over time and characterise
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, programming, algorithms, and data analysis skills Outstanding research skills Applicants with Master degrees by research with technical publications and research experiences in structural dynamics and
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Engineering. Familiarity with partial differential equations (PDEs) numerical analysis and / or data science and statistics will be an advantage. Number of scholarships: One Contact person: Associate Professor
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Geophysics at Curtin University in Perth, Western Australia, offers an exciting PhD research opportunity in the area of active and passive seismic data analysis. The PhD candidate will be involved in
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explore unconventional ideas, develop computer algorithms for data analysis, create new experimental approaches, and apply the technique in areas like biomedicine, materials science, and geology. My group
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the economic analysis of health and health care. We have the highest concentration of economists working in health in the Asia-Pacific region and the largest Health Economics PhD program in Australia, reflecting
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conducted. Second, the project will use a task analysis methodology (Sharbanee et al., 2019; Greenberg, 2007) to create a sequential model of the process that couples go through to resolve imbalances in
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Status: Closed Applications open: 1/07/2024 Applications close: 18/08/2024 View printable version [.pdf] About this scholarship Description/Applicant information Project Overview The concept of individualisation of training to maximise the adaptive response is as important for team sport...
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on testing the sensitivity of an Australian collection of E. necator isolates to a combination of both new and older DMI fungicides. This analysis will allow for the establishment of different sensitivity
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. Once the models are incorporated into a single System Architecture it will be analysed. The analysis will look at: the limits of the models. This will help to identify what has been and has not been