136 computer-"https:"-"APOS-UFFICIO-CONCORSI-DOCENTI" "https:" "https:" "https:" "https:" "J. F" positions at Ulster University
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research methodology is coupled CFD (Computational Fluid Dynamics) and FEM (Finite Element Method) modelling and simulations. This is the only methodology allowing simulations of fluid-structure interaction
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criteria which requires that they have lived in the EEA, Switzerland, the UK or Gibraltar for at least the three years preceding the start date of the research degree programme. Applicants who already hold a
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the EEA, Switzerland, the UK or Gibraltar for at least the three years preceding the start date of the research degree programme. Applicants who already hold a doctoral degree or who have been registered
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', Department for Agriculture, Environment and Rural Affairs, Published 16 December 2013, [Online] Available at: https://www.daera-ni.gov.uk/publications/review-waste-disposal-mobuoy-site-and-lessons-learnt
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programme. Applicants who already hold a doctoral degree or who have been registered on a programme of research leading to the award of a doctoral degree on a full-time basis for more than one year (or part
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Apply and key information This project is funded by: North South Research Programme (NSRP), funded through the Shared Island Fund Summary Applications are invited by Ulster University for a PhD in
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, regardless of residency or domicile. Applicants who already hold a doctoral degree or who have been registered on a programme of research leading to the award of a doctoral degree on a full-time basis for
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on a programme of research leading to the award of a doctoral degree on a full-time basis for more than one year (or part-time equivalent) are NOT eligible to apply for an award. *Part time PhD
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., Ntoa, S., Salvendy, G. (eds) HCI International 2023 Posters. HCII 2023. Communications in Computer and Information Science, vol 1833. Springer, Cham. https://doi.org/10.1007/978-3-031-35992-7_2 Familoni
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Summary Positioned within Ulster University’s School of Computing, this research theme explores the integration of artificial intelligence with quantum technologies to advance next-generation