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for 129Xe MRI Development of image reconstruction techniques for novel 129Xe pulse sequences Supervising undergraduate and junior graduate students, and technicians in the lab Developing, writing, and editing
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-light three-dimensional reconstruction, computational photonics and AI-assisted sensing. The role will focus on developing optical encoding methods, imaging-system calibration approaches, reconstruction
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management, environment reconstruction, target imaging, or radio-resource management. This is a industry-facing role combining advanced technical research, simulation development, pre-standardisation
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management, environment reconstruction, target imaging, or radio-resource management. This is a industry-facing role combining advanced technical research, simulation development, pre-standardisation
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procedures. The doctoral candidate will combine non-invasive electrocardiographic imaging (ECGi) with late gadoliniumenhanced magnetic resonance imaging (LGE-MRI) to create personalised models of cardiac
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scattering, computational imaging, and intelligent sensing. Develop novel theories, methodologies, and technologies for high-resolution imaging, information reconstruction, and target characterization in
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, large language models, AI agents, and 3D reconstruction techniques to generate structured digital representations from multimodal data and support infrastructure monitoring, management, decision-making
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-particle Electron Microscopy (cryo-EM), including data acquisition, image processing, three-dimensional reconstruction and structural analysis Practical experience in a biochemical laboratory and/or handling
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initial imaging modality. The postholder will develop computational pipelines and AI models for multimodal image reconstruction, enhancement, fusion and validation. They will also contribute to benchmarking
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imaging, medical signal processing, beamforming, image reconstruction, elastography, Doppler imaging, or computational imaging. Demonstrated experience in algorithm development and scientific programming