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Laboratoire de Physique des Interfaces et des Couches Minces (LPICM), UMR CNRS/École Polytechnique, | Palaiseau, le de France | France | 10 days ago
multidisciplinary team involving image processing labs (e.g., CMAP) and French hospitals (e.g., CHU Kremlin-Bicêtre, Hôpital Foch, Institut Mutualiste Montsouris, Institut Gustave Roussy). Phase 1: Design and develop
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(e.g., tensor or multi-modality data). Work with other researchers and PhDs to develop AI applications related to image processing, computational imaging as well as computer vision. Lead a team of junior
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hospital intensive care unit. The post holder will have primary responsibility for the development and evaluation of the system, and of the data processing and image display software. The post holder will
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(e.g., tensor or multi-modality data). Work with other researchers and PhDs to develop AI applications related to image processing, computational imaging as well as computer vision. Lead a team of junior
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necessary lead relevant meetings. To undertake any other duties relevant to the programme of research. Job Requirements: PhD degree in Computer Engineering, Computer Science, Electronics Engineering or
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computing. With extensive experience in medical image analysis, computer vision, and AI systems through collaborations with leading institutions. Key Responsibilities: Conduct advanced research in the areas
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, operation of the scanner, data acquisition and analysis, image evaluation, and statistical analysis. The fellow will also be expected to prepare manuscripts and conference abstracts related to projects and
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the academic promotions process. About You Completed PhD (or equivalent experience) in Mechanical Engineering, with an established profile and over 10 years of professional experience in mechanical or opto
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workflows. (Preferred) Basic skills in microscopy image analysis and quantitative data processing. To Apply Applicants should submit: A CV including publications A cover letter describing relevant experience
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in image processing, quantitative analysis, and biological interpretation Proficiency in AI/machine learning tools for image segmentation, transformation, registration, or tracking Solid mathematical