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to the POSSEM trial, using photon-counting coronary CT angiography, advanced imaging, and computational modelling to identify patients at risk of accelerated coronary artery disease and enable more personalised
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at the Department of Cell and Molecular Biology. The Elf group works across traditional disciplinary boundaries to explore life at the molecular level. We build physical models of key biological processes and develop
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/ Postdoctoral Researcher to join an 18-month NTU–industry project on AM-enabled optimisation of drag-reduction devices for maritime vessels. The successful candidate will design and prototype test articles
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of Position Temporary Position Time Status Full-Time Required Education Bachelor’s Degree Required Related Experience Some knowledge and interest on image processing software (e.g., Pix4D, QGIS, ARQIS
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. The research involves developing a new generation of radiation detectors that can make medical imaging safer and more effective. The focus of this project is to scale-up the detectors from research-level single
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++, Matlab. Experience in imaging data processing. Other Requirements Ability to interact with laboratory animals. Contact with patients and/or human research subjects. HIPAA Training required. Equal
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in academic writing Possess good critical thinking skills Show strong initiative and take ownership of work Interest in AI, machine learning, image/audio processing
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for generating high‑quality diagnostic images and enabling precise visualization of biological processes at the molecular level. Working in close collaboration with scientific partners, the project aims to refine
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this condition. You will evaluate their interactions using in vivo micro-CT, intravital imaging, spatial transcriptomics and molecular analysis techniques, identifying the key pathways governing this process
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Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial | Portugal | 20 days ago
Engineering, Computer Science, or Bioengineering. Knowledge of image processing and image analysis, preferably applied to medical imaging (e.g., segmentation, feature extraction, geometric reconstruction