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Embark on a ground-breaking PhD project harnessing the power of Myopic Mean Field Games (MFG) and Multi-Agent Reinforced Learning (MARL) to delve into the dynamic world of evolving cyber-physical
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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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world-leading or internationally excellent in its quality. Every year Cranfield graduates the highest number of postgraduates in engineering and technology in the UK (Source: Higher Education Statistics
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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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University of Oxford. At a glance Application deadline12 Jun 2024 Award type(s)PhD Start date30 Sep 2024 Duration of award4 years EligibilityUK, Rest of world Reference numberSATM491 Entry requirements
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EligibilityUK, EU, Rest of world Reference numberSATM490 Entry requirements Applicants should have a first or second class UK honours degree or equivalent in engineering or management or related discipline and
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and management. Research Excellence Framework 2014 (REF) has recognised 81% of Cranfield’s research as world leading or internationally excellent in its quality. Every year Cranfield graduates
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deadline22 May 2024 Award type(s)PhD Start date30 Sep 2024 Duration of award4 years EligibilityUK, Rest of world Reference numberSATM475 Entry requirements Applicants must have a B.Sc. in engineering or a
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of world Reference numberSATM459 Entry requirements We are inviting applicants with a minimum of a 2:1 first degree in a relevant discipline/subject area such as engineering, manufacturing, computing, data
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year EligibilityUK, EU, Rest of world Reference numberSATM405 Entry requirements Applicants should have an equivalent of first or second class UK honours degree or equivalent in Mechanical Engineering