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of Computer Science, Norwegian University of Science and Technology (NTNU). The position offers the opportunity to work on cutting-edge research at the intersection of deep learning and computer systems. The successful
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, relating to craniofacial identification research and machine learning. You will require a computer science background. You will be applying AI and/or machine learning to Face Lab processes in relation
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learning frameworks (e.g., PyTorch). Core Knowledge: A strong foundation in machine learning and/or computer vision. The candidate should have a specific interest in test-time adaptation, autonomous AI
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for the position. Preferred selection criteria Experience with machine learning and neural networks Basic knowledge of MR physics Experience with signal processing and/or image processing Experience with Linux
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of video and low-cost sensor technologies to capture subtle movement patterns, creating a rich dataset for AI-driven analysis. Machine learning, deep learning, computer vision and multimodal AI methods will
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University of Science and Technology (NTNU) has a vacant position as PhD candidate in the field of machine learning for materials science. Your immediate leader will be the Head of Department. About the
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, algorithms, visual computing, AI, databases, software engineering, information systems, learning technology, HCI, CSCW, IT operations and applied data processing. The Department has groups in both Trondheim
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considered. Education related to Artificial Intelligence (AI), robotics programming, computer vision, Design for Manufacturing and Assembly (DfMA), or life cycle environmental/cost assessment is considered
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SINTEF, Equinor, and Total. The main objectives of the project include the development and the integration of signal processing and machine learning methodologies aiming to improve flow assurance via field
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at the intersection of AI, deep learning, computational neuroscience, and vision science. You'll develop biologically realistic neural networks to understand how individual differences in the brain shape perception