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following areas is desirable: collection and analysis of dense nodal seismic datasets, ambient noise tomography, high-performance computing, machine learning applications in observational seismology, and
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generating fusion energy. This research will focus on the chemical speciation and transport of tritium in the molten salt blankets using ab initio quantum simulations, machine learning potentials, and
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through data-driven modeling and optimization. The successful candidate will work at the intersection of thermal-fluid sciences, control theory, and artificial intelligence/machine learning to advance
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, and remote-sensing data) to support model benchmarking, parameterization, and uncertainty quantification. Explore and apply AI/ML approaches (e.g., machine-learning emulators, surrogate modeling, AI
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University safety requirements. Machines and Equipment: Operational knowledge of laboratory equipment for mechanical testing of concrete materials Operational knowledge of equipment for 3D Printing of concrete
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, and remote-sensing data) to support model benchmarking, parameterization, and uncertainty quantification. Explore and apply AI/ML approaches (e.g., machine-learning emulators, surrogate modeling, AI
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The University of Lincoln is seeking a highly motivated Research Associate with expertise in robotic perception and computer vision to join our internationally recognised Agri-Robotics research team
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expertise in specialised domains where labelled data is scarce. Recent foundation models have transformed computer vision, yet their ability to acquire new expertise remains limited when training data is
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A post-doctoral position is available to take a leading research role in an industry-facing HBLB funded research project entitled “Toward Racehorse Injury Prevention: A Computer Vision-Based
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to industry and developments with Deep Learning (DL), Computer Vision (CV), Transformers, Large Language Models (LLMs), Natural Language Processing (NLP). Mandatory requirements • Bachelor's degree