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Field
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Fellow, you will lead the development of advanced assurance methodologies for the safe use of artificial intelligence (AI) and autonomous functions in human spaceflight systems. Your work will bridge
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the offer, initially planned for November 2026. The PhD candidate is expected to participate in simulation and experimental activities related to autonomous spacecraft systems and validation frameworks
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. • Strong background in autonomous robotic systems, unmanned aerial systems (UAS), or multi-agent robotics. • Demonstrated expertise in one or more of the following areas: o Counter
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synthesis. Experience and knowledge with robotic systems, high-throughput experimentation, or autonomous laboratory development. Demonstrated scientific productivity (peer-reviewed publications). Strong hands
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Supervise and mentor research associates, engineers, and PhD students working on the project Collaborate with perception, controls, systems, and hardware teams to guide integration of learned policies
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Organisation: Cranfield University Faculty or Department: Faculty of Engineering and Applied Sciences Based at: Shrivenham, Oxfordshire - Cranfield Defence and Security Hours of work: 37 hours per
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Organisation Cranfield University Faculty or Department Faculty of Engineering and Applied Sciences Based at Shrivenham, Oxfordshire - Cranfield Defence and Security Hours of work 37 hours per week
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The School of Mechanical & Aerospace Engineering (MAE) is a robust, dynamic and multi-disciplinary international research community comprising of world-class scientists and bright students. MAE
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from YouTube. Accept cookie and refresh page to watch video, or click here to open video) About the position Join a leading research environment in autonomous maritime systems and contribute
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Full time, 1-year fixed term position with possibility of extension Be part of the development of novel quantum magnetometer-based navigation tools for autonomous marine systems Base Salary $117,936