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, C#, Java, Q#, Q language, PennyLane, Qiskit, Quantum Development Kit etc. Please contact Aufeef Chauhan for more information. Potential candidates must have a good hold of distributed software systems
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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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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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methodologies, including quantitative, qualitative, and mixed methods. Innovation: Noble thinking and ability to innovate a new prototype to solve industry gaps in cyber security. Analytical skills: Problem
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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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and verbal communication skills Strong computational, programming, algorithms, and data analysis skills Outstanding research skills Capacity to work independently and as a part of a team Applicants with
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pipelines to analyse big volumes of metagenetic data. The analysis pipeline will roughly use packages such as trimomatic, FastQ screen, centrifuge/kraken and many more. The PhD candidate: The preferred PhD