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by developing AI methods that improve recognition of rare species while providing reliable measures of uncertainty. Using state-of-the-art computer vision approaches — vision transformers, self
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learning and experience in two or more of: computer vision, sensors/sensor fusion, robotics fundamentals. • Proficient in programming languages such as Python and C++; experience with frameworks such as
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interdisciplinary training, suitable for candidates from biochemistry, molecular biology, computational biology, chemistry, or data science backgrounds. You will gain experience in: Molecular modeling, QM/MM & MD
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This PhD project focuses on advancing computer vision and edge-AI technology for real-time marine monitoring. In collaboration with CEFAS (the Centre for Environment, Fisheries, and Aquaculture
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in AI. Previous publication record in relevant fields: AI, machine learning, computer vision, etc. Previous successful project on a relevant topic. Good knowledge of statistics, probability
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Exciting Fully Funded PhD: Computational Modelling for High-Pressure, Low-Carbon Storage Technologies. Be a Key Player in Shaping the Future of Clean Energy Storage! School of Mechanical, Aerospace
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the central challenge hindering this vision: the fundamental incompatibility between text-native LLMs and the operational reality of computer networks. Directly applying LLMs is impeded by three core technical
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28 Nov 2025 Job Information Organisation/Company Queen's University Belfast Department Centre for Secure Information Technologies Research Field Computer science » Cybernetics Engineering » Computer
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About the Project Project details: The rapid evolution of battery technologies drives global lithium demand, and the UK’s 2030 vision seeks a competitive, sustainable battery supply chain to fuel
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Peter Hamilton, and Professor Ray Yep), and who also share a vision for public engagement of the discipline. The studentship is funded by an endowed fund at the University. The Centre encourages and