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Field
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working at the intersection of computer vision, and 3D AI for the built environment. Our goal is to transform how physical environments and infrastructure are captured, analyzed, and monitored using
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Vision Group (PVG) at McGill University and Mila—Quebec Artificial Intelligence Institute, led by Prof. Tal Arbel, seeks Postdoctoral Fellows to advance causal-temporal and probabilistic modeling, 3D
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disciplines human identification and bite mark analysis. The plan is to extend beyond our research group’s current results and explore quantitative 3D matching of tooth surfaces from related individuals, and
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%) • Curate multimodal real and synthetic datasets, including photogrammetry, LiDAR, and depth cameras, to build scalable analysis pipelines (10%) • Conduct data collection for validation of developed
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for biomarkers in 7T images. - Development of artificial intelligence algorithms and models for the processing and analysis of MRI images/spectra, focusing on the detection of tumor tissue and the quantification
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obtained from ex vivo robotic tests will inform multiscale numerical models of tissue mechanotransduction, calibrated using in vivo murine gait analysis and behavioral tracking provided by IRMB
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segmentation, enabling surgeons to make informed decisions in real-time. By correlating detailed histopathological annotations with 3D reconstructions of US data, we aim to deliver precise, automated tumor
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Job Description If you have extended experience in imaging and imaging analysis from two- and three-dimension (3D) cell culture and your aspiration is to be at the forefront of system biology and
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parallel channels—manual signs, spatial grammar, facial expressions—operating simultaneously in 3D space, presenting unique computational challenges for cross-modal alignment. The project will pioneer new
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If you have extended experience in imaging and imaging analysis from two- and three-dimension (3D) cell culture and your aspiration is to be at the forefront of system biology and single-cell