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Field
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, preferably in Python, and experience with machine learning or deep learning. Experience in computer vision, digital pathology, whole-slide image analysis, self-supervised learning, foundation models, multiple
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related field at the level of a master degree Programming skills (Python) and experience with common machine learning platforms Experience with deep learning, computer vision, medical image analysis
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integrating AI with vision at the edge. Despite recent advancements, the synergy between AI and computer vision remains constrained by fundamental imaging bottlenecks. Conventional HDR techniques frequently
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. The project is an interdisciplinary collaboration between the MRI Physics Group and the X-ray Physics Group at the Department of Physics. In the MRI Physics Group, we aim to improve image quality in medical
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applied to computer vision and image analysis. Analytical thinking and problem-structuring skills, including the ability to abstract complex systems, identify core research challenges, and develop
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of novel volumetric representations and computational imaging methods for paired visible-light and X-ray images, as well as extending computer vision techniques from the visible-light RGB photography domain
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with a group of ~3–4 people, as part of a microscopy team of ~25 people, as well as interactions with collaborators at the Institut de la Vision (Paris). École Polytechnique is located in the Paris
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the development of novel volumetric representations and computational imaging methods for paired visible-light and X-ray images, as well as extending computer vision techniques from the visible-light RGB
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system integrates robotics, automated sample handling, sensor networks, imaging systems, cloud computing, and machine-learning-based analytics. The research work at NTNU will focus particularly
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candidate will benefit from a network of European experts in different fields (gene therapy, pharmacology, bioinformatics, disease modeling, imaging) and will have the possibility to visit other labs in