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/deep learning-based medical image analysis methods for computerised tomography scans (CT scans). Key applications of such ML/DL methods are illustrated by our prior research (PMIDs 33913675, 33234786
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studies (GWAS), fine-mapping, colocalisation, polygenic risk scoring, and Mendelian Randomisation; and (ii) deep phenotyping of multi-modal cardiovascular imaging (MRI, CT, echocardiography) from large
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strong technical expertise in deep learning, such as models for image segmentation, classification, multi-modal processing, foundation models, or agentic frameworks. An extensive background in computer
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, biomedical engineering, medical imaging, or related field Experience in deep learning with practical implementation Strong Python skills and relevant frameworks Experience with large clinical imaging datasets