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5.2: Deep Eutectic Solvents (DES) are increasingly being studied for their potential role in lithium-ion battery recycling. DES has limitation for industrial application due to its poor performance in
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Job no:517186 Work type:Fixed term - Full-time Campus:Adelaide Categories:Level A, Level B (Level A/B) $102,024 to $135,932 per annum plus an employer contribution of 17% superannuation applies
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of the barriers that people with disabilities face at school, university, work and in the social sphere. Our work is guided by on-the-ground partnerships with the community to ensure we’re addressing real problems
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Multiple PhD Scholarships available - Cutting-edge research at the frontiers of Whole Cell Modelling
at Monash University has multiple PhD Scholarships available to work on some exciting projects. Conduct cutting-edge research at the frontiers of Whole Cell Modelling! Projects include: Integrative Modelling
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, professional development training and opportunities for industry engagement. Monash Arts is a diverse and vibrant faculty which advances disciplinary, multi- and inter-disciplinary research that operates at a
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operations, ensuring you will be surrounded by talented colleagues, many world-leading. Our work's cutting-edge nature - not just in your own area, but across virtually the full spectrum of human endeavour
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top up of $10,000 per year for a maximum of 3.5 years. As the scholarship recipient, you will have the opportunity to work with a team of leading researchers, to undertake your own innovative research
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. This process operates under ambient conditions, utilises water as a hydrogen source, and is powered by renewable electricity. Recent advances in electrocatalyst design – enabled by operando spectroscopic
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Acknowledgement of Country CSIRO acknowledges the Traditional Owners of the land, sea and waters, of the area that we live and work on across Australia. We acknowledge their continuing connection
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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