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of the Hub. Our approach enhances T2 (Interconnected QC systems) through verification methods for connected networks, supports T1 (Integrated quantum demonstrators) via hardware-agnostic metrics, and enables
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Deadline: 30 September 2025 A fully funded four-year PhD position is available to work on the project titled “Real-world quantum verification and benchmarking of noisy hardware”. This position is a
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of the Hub. Our approach enhances T2 (Interconnected QC systems) through verification methods for connected networks, supports T1 (Integrated quantum demonstrators) via hardware-agnostic metrics, and enables
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Deadline: 31 August 2025 A fully funded four-year PhD position is available to work on the project titled “Real-world quantum verification and benchmarking of noisy hardware”. This position is a
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Liverpool where, in the School of Computer Science and Informatics, we have an active group of PhD students, postdocs, and academics working at the intersection of Machine Learning, Verification and
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findings to academic and industrial audiences, publish in leading journals, and actively contribute to the development and dissemination of open-source software. Additionally, you will support junior
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into areas such as AI-driven verification, predictive maintenance, and compliance assurance, aiming to enhance system reliability and safety. Situated within the esteemed IVHM Centre and supported by
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-verification, and in-country assessments of the nature, extent and likelihood of threats to these heritage sites. MAEASaM is a partnership programme, with the University of Cambridge serving as the lead and
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://doi.org/10.1021/acssuschemeng.4c01820 ). The PhD candidate will then push the boundaries by developing and optimising the technique further, integrating with advanced instrumentation and custom software
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interest and research in the field of economic and experience in data management and analysis. Demonstrable experience of working with quantitative data and relevant software (Stata, R, Python, or similar