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Field
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systems using computer vision, quantitative image analysis, deep learning methods for detection, diagnosis, and quantitative analysis of abnormalities with multimodal data, including clinical and
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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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programme grant “Total Body Nuclear Imaging for the Development of Nanotheranostics”. This Programme involves 15 co-investigators in a range of disciplines related to PET imaging strategies
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will work closely with the Principal Investigator (PI), Co-PI, and the research team to develop deep learning-based computer vision algorithms and software for object detection, classification, and
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Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial | Portugal | 6 days ago
Engineering, Computer Science, or Bioengineering. Knowledge of image processing and image analysis, preferably applied to medical imaging (e.g., segmentation, feature extraction, geometric reconstruction
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management/administration processes Desirable Experience working with Drosophila, live calcium imaging, Matlab/Python programming and/or behaviour A good publication record in neuroscience. Further details
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machine learning, computer vision, and medical image analysis, with publications in top-tier AI and medical image analysis conferences and journals, including CVPR, ICCV, ECCV, NeurIPS, MICCAI, TPAMI, TIP
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of Biomedical Engineering (SBME). The successful candidate will work on advanced machine learning applications in computational pathology, medical imaging, and clinical text analysis. They will be expected
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research grants in the above areas Job Requirements: A PhD degree in Computer Science, Data Science, Engineering, or a related field. Research experience in Computer Vision, Image Processing, Multimedia
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The School of Materials Science and Engineering (MSE) provides a vibrant and nurturing environment for staff and students to carry out inter-disciplinary research in key areas such as Computational