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publication Strong programming skills and familiarity with machine learning or finite element modelling Not currently receiving another scholarship of equal or higher value Application process Future student
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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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) + Finite element methods for complex flows in porous media (generalized multiscale finite elements via autoencoders, adaptive in space and time, splitting methods, and variational flux recovery) + Adaptive r
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analysis 2. Determine how consumer cognitive load affect ad-skipping behaviour by using pupillometry 3. Explore and identify the ad characteristics and elements that engage consumers by using skin
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of proven academic excellence and will have already made significant personal contributions to their discipline. They will have gained high-level experience with a research component through studying
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Australian police custody and young people. The project is a component of Dr Shelley Walker’s Australian Research Council (ARC) Discovery Early Career Research Award (#DE240101056 ). The National Drug Research
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strengthen their applications by demonstrating strong research potential, which may include: Completion of a degree with a substantial research component (at least 25%), such as an Honours degree or higher
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collection, existing genomics data and a dedicated allowance at Pawsey for bioinformatics analysis. The skills learnt during this project will be transferable to any field of mammalian biology. Any information
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policymakers. Through this experience, Fellows will enhance their understanding of global governance, expand their professional networks, and develop valuable skills in policy analysis and legal diplomacy. By
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. Utilise SQL or other database query languages to extract and manipulate data as needed for analysis. Perform innovative statistical analysis to contribute to identifying data patterns and trends. Who we