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are looking for a motivated and capable researcher who is eager to grow into this opportunity. The selection panel will use the following criteria: Familiarity with crop simulation models (e.g. APSIM, DSSAT
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I specialise in the numerical modelling of high-energy particle collisions , such as those occurring at the Large Hadron Collider. Accordingly, most projects I offer straddle the intersection
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anticipate the student will use statistical methods that include descriptive statistics, generalised linear models (GLMs) and structural equation models (SEMs). Supervisors: Professor Deb Loxton and Professor
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Metallurgy and Corrosion cluster, working within a multidisciplinary team spanning theory, advanced characterisation, and computational modelling. This environment provides an excellent platform for developing
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, computational modelling, and data-driven alloy design to: Understand the mechanisms of local austenite-to-ferrite transformation in low-alloy steels; Develop frameworks to predict and control
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environments. Access proprietary market data and institutional infrastructure, including cutting-edge computing environments and live market simulation tools. Translate research into production, contributing
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copy the link to this scholarship website into Question 2 of the Financial Details section. About the scholarship This PhD project will contribute to the development and optimisation of a Paediatric Post
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compartmental models for RSV developed within the STAMP-RSV program by tailoring an established software library for individual simulation to the Australian RSV transmission context. Information to parameterise
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observational research (e.g., simulations) and/or lab or field experiments Experience with the analysis (e.g., sequential analysis, multilevel modelling) and interpretation (e.g., conference presentation
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to trick AI-based models, pay little attention to fake-normal data traffic generated by Generative Adversarial Networks (GAN). This PhD research will address a major vulnerability in AI based smart grids by