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Infrastructure? No Offer Description Area of research: PHD Thesis Job description:PhD Position - Denoising Methods for Dual-Tracer PET Imaging Positron emission tomography (PET) is often used to diagnose
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humanities. We combine terahertz, ultrasound, infrared thermography, hyperspectral/multispectral, and X-ray imaging with multimodal data fusion, interactive visualisation, and digital twins. Results
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and share research findings with colleagues in partner institutions, and research groups. You must be working towards a PhD in molecular imaging and experience working with PET imaging. Experience with
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. Activités The PhD will employ a combination of simulation, optical engineering, and experimental validation: • Imaging processing and control algorithms: Use and develop existing coronagraphic simulation
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of this programme. The profile PhD in computer vision, computational biology, physics or a related discipline Demonstrated expertise in image analysis and working with large-scale imaging datasets Strong expertise in
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-field imaging of dynamic processes" "Multi-scale X-ray speckle-based imaging" "Spectral X-ray speckle-based imaging" "Single-shot multi-projection X-ray phase-contrast imaging" "X-ray virtual histology
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SOPs, QA/QC processes, and rigor/reproducibility frameworks consistent with CCSG expectations. · Implement harmonized imaging protocols to support longitudinal tumor studies and collaborative
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | about 2 hours ago
Engineering, Computer Science, Applied Mathematics or a related field. - A strong background in image processing or/and in computer vision is required. - Strong programming skills in Python. - Strong
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at the tumour margin represent a key target for earlier and more effective therapeutic intervention. This PhD project will develop advanced MRI analysis methods and imaging-driven predictive models focusing
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scientists, applied mathematicians, and computational scientists, and building worldwide collaborations aimed at tackling the challenges posed by terabyte and petabyte-scale imaging data processing