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expertise in MRI physics, obstetrics, placental biology, biomedical engineering, mathematics, computer science and artificial intelligence. The team includes researchers from the University of Nottingham
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computational architectures for foundation models, explore embodied AI approaches, and pioneer self-improving methodologies that push the boundaries of intelligent systems. Key Responsibilities: Lead
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intelligence (AI) technologies for defect detection, image/video analysis and understanding. Perform system integration of the developed algorithms Oversee project budget and coordinate the procurement and
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to developing the next generation of resilient robotic networks for critical maritime operations. As a PhD candidate, you will work at the intersection of robotics, artificial intelligence, and autonomous systems
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questions relevant to agriculture or similar scientific fields (e.g. ecology, geology, genomics). Theoretical understanding of the application of modelling, simulation or artificial intelligence
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agriculture. The vision of the agency is to provide global leadership in agricultural discoveries through scientific excellence. ARS’s SCINet/Artificial Intelligence (AI) Center of Excellence Research
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(ESMs) and climate prediction systems underpin modern climate prediction but running them at impacts-relevant resolutions is computationally expensive. Artificial Intelligence (AI) offers new
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artificial intelligence (AI) has shown great promise in helping us identify patterns, make predictions, and drive innovation in manufacturing, understanding how some AI models make their predictions
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timely research question: How can Large Language Models (LLMs) and intelligent agents support transparent, scalable, and auditable clinical data harmonization? We are particularly interested in: LLM-driven
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or more of the following areas: robotic mobility or manipulation, embodied intelligence, self-reconfigurable or compliant robotics, force or tactile sensing, intelligent control, multibody modeling