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This project will investigate artificial intelligence (AI) to improve weather forecasts and use crop models for making better farming decisions. The expected outcome is protocols for integrating AI
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PhD Scholarship – Modelling the social and political drivers of net zero transitions Job No.: 670767 Location: Clayton campus Employment Type: Full-time Duration: 3.5-year fixed-term appointment
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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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understand its fundamental causes has been limited to animal models and trials. There are over 27 animal models for neuropathic pain where pain has been induced by macroscopic & microscopic nerve lesions
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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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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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@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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of potential options for implementation. This will include prototyping and testing of various implementation options, analysis and documentation of results. Project 2 - Future Power System Modelling: As part of
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models like SWMM are computationally slow and lack scalability, while opaque AI methods risk biased outcomes. This project addresses these gaps by developing a responsible machine-learning framework