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PhD Scholarship Opportunity: Secure Quantum Computation on Shared Quantum Processors in Clayton campus
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This project offers an unprecedented PhD research opportunity to work on secure quantum computations on a shared quantum processor. Quantum computing is an emerging area of research with potential for revolutionary industry applications. In the near-term, the access to quantum processors is provided through shared environment via cloud systems. In this model, many users access the same quantum processor to perform their computing jobs. However, such shared environment poses a serious security vulnerability where an adversary can create cleverly selected sequence of quantum gates interfering with the computing jobs by other users leading to wrong answers. Similar security issues have been detected in the process of quantum error correction or software level compilations. In this project, PhD student will analyse security vulnerabilities of shared quantum computers and develop software level solutions to ensure secure and reliable sharing of quantum compute resources.
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PhD Scholarship Opportunity: Scalable Artificial Intelligence Decoding for Quantum Error Correction in Clayton campus
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Quantum computers suffer from noise or errors which significantly reduce their fidelity to perform large-scale useful computations. To overcome errors, quantum error correction protocols are implemented which detect and correct errors using classical processing known as Decoding. However, decoding must be completed at fast speed and large-scale to ensure errors are fixed before they accumulate. In this project, the student will develop scalable artificial intelligence based methods such as deep neural networks or transformers to perform decoding in microsecond time scales while processing error information from millions of qubits. The project will lead to a timely and critical development for rapidly advancing quantum computing industry and play an important role in enabling real-world applications of quantum computers.
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PhD Scholarship Opportunity: Quantum Compiler for Efficient Circuit Transpilation in Clayton campus
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This PhD project will develop efficient quantum compiler methods to bridge the gap between quantum algorithms and their execution on quantum processors. The project will develop innovative quantum software components and reinforcement machine learning models to enable efficient transpilation of quantum circuits on a wide range of quantum processor modalities and topologies. The key aim of the project is to minimise resource requirements (number of qubits, gates, etc) for quantum circuit execution.
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Indigenous Research Fellow (Identified) in Clayton campus
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Lead Indigenous research advancing culturally safe, intersectional outcomes for Aboriginal and Torres Strait Islander academics.
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Doctor of Philosophy (PhD) in Machine Learning for In Situ Materials Characterisation in Clayton campus
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We are seeking an outstanding PhD candidate to develop machine learning methods for advanced and in situ materials characterisation. Modern characterisation techniques generate increasingly complex datasets describing microstructure, crystallography, phase evolution, chemistry and morphology.
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