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for transformational research and education in technology and management. Research Excellence Framework 2021 (REF) has recognised 88% of Cranfield’s research as world-leading or internationally
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of more sustainable and safer aerostructure in next generation aircraft. It will impact research strategies and technology for maintenance regime and service operations in the future. The researcher gain
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facilities and interact with experts in Human Factors Integration (HFI), systems engineering, and system modelling. The research will culminate in developing software tools and engaging with a robotic testbed
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This research opportunity aims to hire PhD students as a self-funded program. By analysing retinal images with deep learning technology, early detection of Alzheimer’s disease may be possible. By
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Industry 5.0 goals. Expect impactful insights into advanced technology integration and human expertise, driving sustainability through improved system performance. Students benefit from collaboration
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for global industries, all while collaborating with experts in the prestigious International Systems Realisation Partnership. Furthermore, the student will gain invaluable skills in data analysis, problem
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of data driven approaches further relies on the adoption potential and company readiness to use it. This observation likely opens an opportunity for social and behavioural sciences to enable transitions as
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Applicants should have a first or second class UK honours degree or equivalent in a related discipline. This project would suit a student with an aerospace or mechanical engineering background. Experience
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postgraduate university that is a global leader for transformational research and education in technology and management. Research Excellence Framework 2021 (REF) has recognised 88% of Cranfield’s research as
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, these systems serve as complex functional approximators trained over an input-output data set. ‘Second Wave AI’ is the term used to describe the current glut of 'machine learning' style intelligence, where