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relevant wear particles and simulating physiological loading conditions. This scholarship aims to develop a spinal implant-on-a-chip platform to study the mechanobiological effects of wear particles on
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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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materials systems at the molecular level with machine learning. The PhD Student will undertake a study analysing mass spectral imaging data streams in real time using machine learning workflows. A pathway for
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materials systems at the molecular level with machine learning. The PhD Student will work with tumour sections to develop multiple instance learning and weak supervision / spatial transcriptomics models
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-page cover letter briefly outlining your interest in the project Evidence of research ability: A digital copy of a Master’s or Honours’ thesis; and a digital copy of academic transcripts A detailed CV
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, supported by the Monash e-Research Centre, for high-performance transport and land use modelling. World-class transport modelling and simulation platforms (Driving Simulator, Data Visualisation Lab
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Computer Systems Engineering ● Materials Science and Engineering ● Mechanical and Aerospace Engineering For further information, please follow the link for each Graduate Research Degree ● 3291 - Doctor
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and Computer Systems Engineering ● Materials Science and Engineering ● Mechanical and Aerospace Engineering To be eligible to apply for domestic postgraduate research scholarships an applicant must be
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: The proposed project aims to enhance the sustainability and transparency of the battery materials supply chain by integrating Environmental, Social, and Governance (ESG) criteria and Life Cycle Assessment (LCA
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sustainability in the TiO2 and mineral sands industry sector. Supporting the circular economy through recovering valuable minerals from the waste streams is a priority for the company. Tronox has a number of