74 postdoctoral-image-processing-in-computer-science positions at Cranfield University
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trustworthy operation of navigation systems in complex, GNSS-denied scenarios. The ultimate goal is to provide the navigation research community and industry with tools and methods that ensure continuous, high
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at leading international conferences and publish in top-tier journals. The successful candidate will gain advanced expertise in multi-sensor fusion, signal processing, machine learning, and positioning
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This self-funded PhD opportunity sits at the intersection of several research domains: multi-modal positioning, navigation and timing (PNT) systems, AI-enhanced data analytics and signal processing
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, mechanical or civil engineering, human factors, computer science, marine operations, or applied physics. An interest in simulation modelling, data analysis, or AI-based decision systems would be beneficial
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future hydrogen fuel cell powered aircraft. Join our diverse and inclusive team to transform the future of aviation as part of the Centre for Propulsion and Thermal Power Engineering. Offering fully funded
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-generation secure computing. With rising industry demand for AI-electronics expertise, graduates will be well-positioned for roles in cutting-edge research, technology development, and industrial applications
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: • Experience with programming (Python, MATLAB), • background in aerospace, computer science, robotics, or electrical engineering graduates, • hands on skills in implementation of fusion
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, ultimately optimising the deposition process. Additive manufacturing (AM) is a rapidly advancing technology, driving numerous innovations and finding diverse applications across industries such as aerospace
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and controlling defects and lay the foundation for a thermal physics-based approach to process qualification. Additive manufacturing (AM) is a rapidly evolving technology that continues to drive
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are assessing the potential of combined granular activated carbon (GAC) and ion exchange treatment to remove PFAS from water sources used for drinking. Part of the planning process involves evaluating operational