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PhD Scholarship Opportunity: Scalable Artificial Intelligence Decoding for Quantum Error Correction
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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
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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)
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Clayton campus
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Level B ($123,138 - $146,228)
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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
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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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Doctor of Philosophy (PhD) in Physical Metallurgy of Hydrogen-Based Iron Oxide Reduction
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Clayton campus
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| We are seeking an outstanding PhD candidate to investigate the physical metallurgy of hydrogen-based iron oxide reduction, with applications to low-carbon and green ironmaking. The project will investigate how phase transformations, reduction pathways and microstructure evolution interact during the conversion of iron oxides to metallic iron. |
