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for the capture, processing, and dissemination of 3D digital twins of cultural artifacts using cutting-edge imaging and rendering technologies.
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activities relating to 3D/4D X-ray micro-tomography image quantification using machine learning tools. The employment will be at the Department of Solid Mechanics at Lund University and the work will be
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In this role, you will help develop and implement cutting-edge AI solutions for real-time, image-guided medical applications, with a focus on advanced robotics. You will work directly with clinical
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innovative methods for processing and analyzing 7Tesla MRI images of different modalities and formats (NIFTI, DICOM, etc.) using machine learning and artificial intelligence techniques. These methods will be
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Translating deep learning models into clinical settings Experience developing deep learning models for real-time image/video segmentation, object tracking, 3D reconstruction, super-resolution. Have a passion on
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models for reliable predictions, along with uncertainty estimates. Advancing multimodal foundation models (images, text, clinical data), temporal 3D generative models for longitudinal MRI, and MLLMs
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settings Experience developing deep learning models for real-time image/video segmentation, object tracking, 3D reconstruction, super-resolution. Have a passion on obtaining external funding and project
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First Team FENG no. FENG.02.02-IP.05-0045/23 entitled " Development of a two-component hybrid bioink for 3D bioprinting vascularized constructs ", carried out within the First Team programme of
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research funding than all other New Jersey universities and colleges combined. Rutgers manages Protein Data Bank (PDB), the global archive of 3D structure data for large biological molecules (proteins, DNA
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healthy tissues using both US images and histopathology. Integrate multimodal data: Align histopathology slides with 3D ultrasound reconstructions. Refine imaging technology: Explore improvements in