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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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18th October 2026 Languages English English English The Department of Physics has a vacancy for a PhD Candidate in AI-assisted medical imaging with MRI Apply for this job See advertisement Are you
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computational image analysis, computer vision and machine learning. The aim is to develop robust and standardized methods to link structural, mechanical and biological properties to biomaterial performance and
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, and regenerative constructs. The project combines advanced 2D and 3D bioimaging, including micro/nanoCT, confocal microscopy and SEM, with computational image analysis, computer vision and machine
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on developing probabilistic latent-variable methods for large and structured biological data, with applications in genomics, spatial transcriptomics, and fluorescence imaging. High-dimensional and structured
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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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monitoring 96 parallel cell-culture experiments under precisely controlled environmental conditions. The system integrates robotics, automated sample handling, sensor networks, imaging systems, cloud computing
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on developing probabilistic latent-variable methods for large and structured biological data, with applications in genomics, spatial transcriptomics, and fluorescence imaging. High-dimensional and structured
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and structured biological data, with applications in genomics, spatial transcriptomics, and fluorescence imaging. High-dimensional and structured biological data are increasingly common in modern
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scene, and leveraging that understanding for localization and navigation. A robot builds a picture of its surroundings one lidar scan at a time. Each scan on its own says very little; together