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Research Assistant/Associate in Photonics Integration of Graphene and Related Materials (Fixed Term)
optoelectronics, light emission, optical sensing and quantum communications. This is an ambitious research program, with a strong interdisciplinary nature, across photonics, plasmonics, device physics, electrical
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experience and ambitions A Master’s degree (or equivalent) in physics: photonics, AMO physics, quantum optics, or a related discipline; Excellent communication skills (fluency in English) and strong
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emerging photonic microdevices promising to revolutionise computer, communication, and sensing technologies must be performed with unprecedented picometre (one-hundredth of the atomic size) precision
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experience and ambitions A Master’s degree (or equivalent) in physics: photonics, AMO physics, quantum optics, or a related discipline; Excellent communication skills (fluency in English) and strong
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, operational reconstructions of quantum theory, indefinite causal structures, extended Wigner's friend scenarios, and quantum reference frames. The team is embedded within the Quantum Optics, Quantum Nanophysics
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, operational reconstructions of quantum theory, indefinite causal structures, extended Wigner's friend scenarios, and quantum reference frames. The team is embedded within the Quantum Optics, Quantum Nanophysics
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structures. Experimental Characterisation: Validating the manufactured prototypes through a range of advanced materials characterisation techniques (e.g., spectroscopy, optical and scintillation performance
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energy efficiency. Surface treatments and engineered coatings will be explored to improve inter-material interfaces, reduce optical losses, and enhance detector robustness, critical factors to advance
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early ‘prodromal’ stages) is yet to be established in large community settings. This PhD project will examine the effectiveness of AI-based analysis of eye images in predicting cognitive/neurodegenerative
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, this project will further investigate the optical and thermophysical properties of ceramic moulds—critical for predicting heat flux during casting and improving microstructural integrity. The work will explore