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stars, and what are the barriers in identifying these systems observationally. Lastly, we aim to assess and verify theoretical predictions on the effects of properties such as chemical composition
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complete their milestone 1 within 6 month of enrolment and remain enrolled on a full time basis for the duration of the scholarship. Enquiries The PhD supervisory team will involve a composition of some of
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pa Fixed term Ref: 095093 You will join the group of Professor Alessandro Troisi based in the Materials Innovation Factory (https://www.liverpool.ac.uk/materials-innovation-factory/ ) to work on a
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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
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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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: 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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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