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on developing an innovative framework grounded in Design for Dynamic Management, we integrate AI and predictive analytics to enable adaptive decision-making. This PhD research at Cranfield University aligns with
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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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This is a full funded PhD (fees and bursary) in hypersonic aerodynamics in collaboration with EPSRC. The overall aim of the research is to investigate what are the aerodynamic interference
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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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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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market structures. This PhD project focuses on designing a sustainable business or turning an existing business more sustainable by implementing circular practices incurs a range of holistic implications
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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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An exciting PhD studentship opportunity fully-funded by the Engineering and Physical Sciences Research Council (EPSRC) Doctoral Training Partnership (DTP). This project would suit students with a
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social science discipline. Experience in qualitative research will be an advantage. This funded studentship is part of the Connected Waters Leverhulme Doctoral Programme, which is funding up to 18 PhD
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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