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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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(https://www.bookbotkids.com/ ) is an AI-powered platform and app designed to enhance children’s reading engagement and fluency through interactive AI agents using advanced language models. About the
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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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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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: 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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models. TensorFlow or PyTorch is desirable. How to apply To apply, please ensure you have digital copies of the below information: • Curriculum vitae; encompassing any research presentations and/or
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greenhouse gas emissions. Consumer food behaviour – what we eat and how much we waste plays a critical role. (e.g., in Australia, the biggest proportion of food waste is produced at the household level). To
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the areas of experimental and theoretical physics, synthetic, physical and computational chemistry, material sciences and related areas. The Opportunity The OPTEXC IRTG involves 20 academics in Australia and
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recycling: Project 1 (2 PhD students): Cost-Efficient Direct Recycling for Metal Oxide Cathode Materials – These projects focus on developing low-cost, scalable strategies for the direct recycling and
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Roentgen’s Nobel Prize-winning discovery of X-rays enabled us to non-destructively image inside the body, birthing medical diagnostic imaging and revolutionising materials characterisation