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Field
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lead the image processing and computational analysis efforts, developing robust methods to register, segment, and analyse spectral micro-CT data, and — where relevant — advance reconstruction and
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of myocardial fibrosis using 68Ga-FAPI-04 PET/CT (Protein Positron Emission Tomography associated with Computed Tomography using Gallium-68-labeled Fibroblast Activation Inhibitor), integrating multimodal imaging
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working within Theme 3 of the Programme: ‘Image-guided Surgery’ and will involve the synthesis and assessment of novel multimodal nanomaterials for healthcare applications and radiolabel for PET imaging
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preclinical imaging - Proven expertise in quantitative imaging analysis and in signal or image processing - Strong analytical, organizational, and communication skills - Ability to work in interaction with
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Post-Doctoral Position - Medical Image Processing - (240000Y9) Post-Doctoral Fellow Position in Medical Image Processing (Deep Learning for Trauma CT) The Trauma Radiology AI Lab (TRAIL) in
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Contract: Full-time (35 hours per week), fixed term contract for 12 months Role description The Biomedical and Astronomical Signal Processing (BASP ) laboratory at Heriot-Watt University Edinburgh
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for the analysis of hyperspectral imaging data applied to pictorial layers, based on coupling physical radiative transfer models (two-flux and four-flux approaches) with machine learning methods. The researcher will
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on qualifications and experience), with a speciality in statistical image processing to work with Professor Karen Desmond’s research team on the project ‘Polyphonic Singing and Communities of Music Writing in
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‘, bridges the different techniques developed within the cross-area imaging and gives support to all researchers dealing with image processing challenges. By focusing on automation and enabling correlative
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applications for a 12-month position as either a Research Assistant (Level 2) or Postdoctoral Researcher (Level 1) (depending on qualifications and experience), with a speciality in statistical image processing