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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
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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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have or is finishing a bachelor's degree in chemistry, chemical engineering, material science or engineering or relevant fields. Preference will be given to an honour’s student or a master's degree by
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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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: 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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published or produced material which relate to the research project for which the scholarship was awarded. provide a brief report on the benefits of the scholarship and give permission for the University
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: http://www.curtin.edu.au/research/futurestudents/admission.cfm Enquiries Dr Jun Li Associate Professor, School of Civil and Mechanical Engineering, Curtin University E: junli@curtin.edu.au T: +61 8 9266
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herbicide and antimicrobial resistance that threatens the global agricultural and health industries. This exciting project will draw on parallels with drug resistance to investigate a new molecular mechanism
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-quality battery precursors and materials - These projects aim to advance the DES-based battery recycling processes towards the production of high-purity, battery-grade materials, focusing on developing