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Research Associate with expertise in robotic perception and computer vision to join our internationally recognised Agri-Robotics research team. You will work on Vitrum, an ambitious Innovate UK
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, including discrete and continuous decoding of hand and finger activity Develop egocentric computer-vision methods for understanding hands, objects, hand–object interactions, contacts, affordances, and task
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traitement d'images, de computer vision, de clustering et d'apprentissage. Durée du contrat (en mois) 6 Description de l'offre Vous serez accueilli·e au sein de l’IRESNE , institut de la DES, où vous
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AI-based Digital Pathology (AiDP) Programme. The programme focuses on the development and validation of advanced AI methodologies, including image processing, computer vision, and mathematical
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King Abdullah University of Science and Technology | Saudi Arabia, | Saudi Arabia | about 3 hours ago
and fluid properties in the subsurface formations. Therefore, the objectives of this research project include two aspects: (1) based on the cutting-edge technologies from deep learning, computer vision
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large-scale human data (genomes, single-cell and spatial omics, longitudinal biomarkers, computer vision, electronic health data) with cutting-edge AI, we aim to fundamentally transform Parkinson’s
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focusing on integrating multimodal large language models (LLMs) with embodied AI. This position will involve the development and deployment of Vision-Language-Action models for real-world robotic
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. Profile We are looking for a motivated and committed candidate who brings: Mandatory skills Experience with computer vision for motion analysis Master’s degree in Biomechanics, Biomedical Engineering
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machine/deep learning, computer vision, or applied statistics. Solid programming skills in Python and experience with deep learning frameworks (e.g., PyTorch or TensorFlow) Project funding Other Funding
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Associate in Computer Science for a two-year post within CAPTURE-PH, a multi-centre programme using chest CT and artificial intelligence (AI) to improve the diagnosis, phenotyping and prognostic