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under different surrounding environmental conditions. Sponsorship Information and Background Cranfield Defence and Security (CDS) provide unique educational opportunities to the Defence and security
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and economic resilience. This self-funded PhD relates to informed decision-making in End-of-Life product management. The aim is to develop a sophisticated ensemble prediction model tailored
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learning experiences for research professionals from both academia and industry. About You You will have a good level of education overall with a minimum Grade C GCSE in English and Mathematics
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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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mathematical models and geometric optimization algorithms, leveraging AI and genetic algorithms to enhance sensor integration efficiency. Tasks include validating these models and algorithms against various
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, fees and bursary but opportunity to attend conferences and to link with industrial experts in the field. The student is envisioned to further enhance and develop world class skills in AI and Machine
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systems engineering design and processes. It is expected that the researcher works closely with the academic team to develop a novel generative AI-based model and algorithm to research, analyse and optimise
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on their level of abstraction. This PhD aims to develop a common ontology based methodology to address interoperability issues both in the context of new and legacy assets. A breakdown of the objectives with
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, technology, engineering, the arts, and mathematics) or an equivalent international qualification or closely aligned discipline. Ideally, applicants should have suitable organisational experience. All cases
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S.T.E.A.M field (science, technology, engineering, the arts, and mathematics) or an equivalent international qualification or closely aligned discipline. Ideally, applicants should have suitable