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are available in the School of Molecular and Life Sciences at Curtin University, Australia. The successful candidates will work with Associate Professor Guohua Jia on his Australian Research Council (ARC) Future
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Background Scholarship code: IND-25122 Expressions of interest - open until filled. This is an industry-linked PhD scholarship. This scholarship is created by La Trobe University in collaboration with a new cutting-edge quantitative-trading company to push the frontiers of AI-aided...
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to integrate floating offshore wind turbines and wave energy converters to capture wind and wave energy. The hybrid system’s dynamic responses will be investigated and advanced vibration control technologies
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interested in connecting spatial and spectral information to understand complex materials systems at the molecular level with machine learning. PhD Student A will work with tumour sections to develop multiple
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What you'll receive You will receive: a minimum of $30,000 per year, for 3 years a QUT tuition fee sponsorship (for international students). Eligibility You must: fulfil our PhD admission criteria , including English language requirements (an IELTS score of 6.5 or above if English is not your...
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, advanced soil analysis, and modelling. The research involves field work in Western Australia’s unique ecosystems, applying cutting-edge imaging, spectroscopy and molecular techniques, and leveraging machine
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. The project will employ molecular cloning, iPSC culture, single-cell and spatial transcriptomics, proteomics, and epigenetic profiling to define lineage-immune crosstalk in DMG. Outcomes include mechanistic
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dynamic environment with members of the Faculty of Business and Law and several research centres and groups at QUT.
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applied physics other related disciplines. Demonstrated knowledge in at least one of the following areas: porous media flow computational fluid dynamics (CFD) pore-network modelling lattice Boltzmann method
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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