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This PhD Scholarship is funded by 2022 ARC Discovery Project “Modelling temporal evolution in spatial ecology with dynamical point processes". The world is undergoing rapid environmental change
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Optimizing a 3D microfluidic IVD model to study cell responses to wear particles, refining culture conditions, and analysing cytotoxic and inflammatory mechanisms. Optimizing a 3D microfluidic IVD
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This PhD scholarship is for candidates interested in developing culturally inclusive AI by creating methods and datasets to align large language models with global social and legal norms. This PhD
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any prior research and/or relevant work experience Curriculum Vitae Academic transcript Preferable background and/or previous experience or publications in materials science, modelling (across length
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You will explore the nature of metal corrosion inhibitor interactions through advanced molecular modelling and integrate this understanding into the formulation of evolutionary algorithms
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Using finite element modelling (FEM) to simulate different hole configurations and validating these models with cadaveric femur specimens, this study will provide crucial insights to optimise
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@rmit.edu.au Please send your CV to akram.hourani@rmit.edu.au Required Skills: Programming and simulation: strong experience in Python or MATLAB. Mathematical modelling: probability, optimization, or multi-agent
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In the PhD program, you will be involved in working with a multi-disciplinary team. You will be conducting experiments and developing phenomenological models to understand the graphite formation
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machine learning approaches show issues in model performance and efficiency and vulnerability towards the application of noise over a large number of distributed models. These issues should be overcome by
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healthcare organisation, on exploring the convergence of three key mega-trends and the consequential rise of hybrid virtual care models and their application across the APAC region. The three megatrends are (i