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/international/overseas applicants). Applicants should state “3D Computer Vision for Medical Imaging” and the research supervisor (Eleonora D’Arnese) in their application and Research Proposal document. Complete
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students Subject areas Computer sciences Physical & Environmental Sciences Project description The accelerating impacts of climate change—particularly those related to water, such as flooding, coastal
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Bachelors Honours degree (or equivalent) in an appropriate discipline. Ideal candidate will have some prior knowledge in deep learning and computer graphics. Subject Area Medical imaging, biomedical
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unified artificial intelligence (AI) model capable of segmenting 3D medical images from standard clinical scans and generating 3D meshes across multiple imaging modalities. The project will also investigate
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the design and optimization of multistatic and multifrequency radar architectures for near-field 3D imaging. - Contribute to the electromagnetic modeling of radiating systems, wave-object interaction, and
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-related transport phenomena all require precise knowledge of fluid flow dynamics. Advanced experimental methods such as Particle Image Velocimetry (PIV) and 3D Lagrangian Particle Tracking (LPT) provide
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CCS. Your main tasks will include: Processing and imaging the newly acquired high-density 3D seismic dataset and integrating vintage 3D seismic data to image and characterise the geological structures
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the risk of missed defects. Using the power of Artificial Intelligence (AI), this research aims to: - Automate defect detection in complex 3D structural data - Enhance diagnostic accuracy and processing
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are seeking a Ph.D. student to join our multidisciplinary team developing a radical solution for better detection and treatment that uses ultra-thin snake-like robots and advanced optical imaging techniques
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Excellent communication and writing skills in English. Knowledge of basic physics of radiation and nuclear decay Desirable Qualifications: Experience in the operation of medical imaging systems, such as PET