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relativistic quantum information (RQI). This highly challenging PhD experience will offer you the chance to work on world-class research combining quantum information theory with key aspects of quantum field
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, security, and/or machine learning are preferred. To apply, please submit the following documents to Dr Hai Dong (hai.dong@rmit.edu.au). Expressions of interest should contain the following information: A one
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and correlates will differ between younger adults and the elderly, and females compared to males. Methods: The laboratory uses world-class big-data ‘omics’ analysis of blood immune cells, including
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anaerobic microorganisms. Establish uranium uptake kinetics and stability in response to microbial consortia evolution mimicking in a mining site environment. Establish the uranium remediation strategy
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To receive quality recommendation services, online media platform users are commonly required to hand over their personal data, including personal attributes (e.g., age, gender, location, etc.) and
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prior experience in planning and conducting mixed-method research projects, statistical and qualitative data analysis and academic writing are encouraged to apply. Interested applicants are advised
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The PhD candidate will gain intensive knowledge in innovative processing protocols for complex mineral processing, column leaching, and mining site environmental science through hands-on experiments
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The PhD candidate will gain intensive knowledge in innovative processing protocols for chemical sensing and to develop data acquisition system with the Machine Learning (ML) and/or Deep Learning (DL
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This scholarship is jointly funded by a leading computer vision company in Australia and the STEM College of RMIT University. The research includes investigation into automated product quality
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digital leaders. By the end of this PhD project, the candidate will be in demand from majority of mining and supply chain companies. The ideal candidate we are looking for: Passionate about optimisation