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microscopy and SEM, with computational image analysis, computer vision and machine learning. The aim is to develop robust and standardized methods to link structural, mechanical and biological properties
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, preferably in Python, and experience with machine learning or deep learning. Experience in computer vision, digital pathology, whole-slide image analysis, self-supervised learning, foundation models, multiple
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powered by: Cookie Information Nettsiden bruker cookies Vi ønsker at du skal være trygg når du bruker dette nettstedet. Vi benytter cookies for å sikre at du får en best mulig brukeropplevelse og
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strong asset.•Experience in the analysis of high-dimensional biological data (single-cell or spatial transcriptomics, digital pathology or biomedical imaging) is an advantage.•Comfortable working on Linux
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Inria, the French national research institute for the digital sciences | Rennes, Bretagne | France | about 1 month ago
Conference on Image Processing (ICIP), 2025. [7] R. Khabbaz, M. Antonini, S. Kas Hanna, Marker Guess & Check Plus (MGC+): An Efficient Short Blocklength Code for Random Edit Errors, International Symposium
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the operational state of buildings from acoustic and complementary sensor data. By combining multi-microphone acquisition techniques with additional sensing technologies, advanced digital signal processing and
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conditions, by bridging disciplines, from artificial intelligence, microelectronics, neuroengineering and nanoscience, to single-cell, imaging and molecular analysis, functional genomics and cell biology in
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-inspired computing paradigm with the potential to drastically reduce energy consumption while enabling faster inference than conventional digital architectures. A major challenge, however, is the development
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probabilistic digital twins of coronary arteries. The goal is to create patient-specific models that combine anatomical and hemodynamic information derived from routine clinical imaging. By providing quantitative