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Field
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vision and machine learning methods for multimodal imaging and real-time analysis in colorectal cancer screening and treatment. They will contribute to the design of AI algorithms for polyp detection
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PhD fellowship in Computer Supported Cooperative Work (CSCW) PhD Project in Novel Computer Science Teaching Methods considering Neurodiversity, Physical Computing, and Universal design in teaching
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, multimodal imaging, and AI-assisted diagnostics to enable safer and more effective screening and therapy. The postholder will focus on developing and applying advanced computer vision and machine learning
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more effective screening and therapy. The postholder will focus on developing and applying advanced computer vision and machine learning methods for multimodal imaging and real-time analysis in
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learning-based computer vision algorithms and software for object detection, classification, and segmentation. Key Responsibilities Participate in and manage the research project together with the PI, Co-PI
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support PhD candidates in their thesis research Teach courses at bachelor and master level in relevant fields such as artificial intelligence, machine learning, neural networks, computer vision or image
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live in. Your role The PhD position is embedded within the MICRO-PATH Doctoral Training Programme, funded by the Luxembourg National Research Fund. MICRO-PATH, or Pathogenesis in the Age of
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and programming skills and experience of computer vision and machine learning. Previous experience of real time systems development in Python, OpenCV, PyTorch and deep learning are essential. Experience
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research Teach courses at bachelor and master level in relevant fields such as artificial intelligence, machine learning, neural networks, computer vision or image analysis and coordinate the teaching
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aware that an application for a PhD position at NMBU is at the same time an application for admission to a PhD programme at the institution. The documentation that is necessary to ensure