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models, in-house laboratory tests in a wind-wave-current flume (https://research.ncl.ac.uk/amh/ ) and numerical methodology to quantify biofouling impacts on flow-induced vibration phenomena, structural
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computational modelling focused on achieving net-zero goals. Number Of Awards 1 Start Date 1st October 2026 Award Duration 4 Years Application Closing Date 18th February 2026 Sponsor EPSRC Supervisors Dr Amir
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synergistically, similar to how systems work in nature. Experimental work will include the following indicative activities: Designing and developing CAD models of test coupons and other structures Fabrication
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therefore investigate how these variations affect signal detectability and classification performance of AI models for fall detection. The research will combine experimental studies on different floor systems
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. This position provides a unique chance for a highly motivated researcher to contribute meaningfully to innovative computational modelling focused on achieving net-zero goals. Number Of Awards 1 Start Date 1st
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their operational reliability. The PhD student will combine mathematical models, in-house laboratory tests in a wind-wave-current flume (https://research.ncl.ac.uk/amh/ ) and numerical methodology to quantify
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requirements: Excellent analytical skills Strong verbal and written communication skills Desirable: Strong proficiency in optimising and modelling power and energy systems Programming skills in Python and Julia
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the Ven Te Chow Hydrosystems Laboratory at UIUC, using 3D-printed riverbed models derived from field data. Finally, insights from experiments will be incorporated into cutting edge flood models to enable
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. There will be scope for both observational and theoretical work, as we develop ever more sophisticated reverberation mapping models that account for general relativistic and radiative transfer effects, and
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evolve under and after mining. These observations will be complemented by physical experiments in the Ven Te Chow Hydrosystems Laboratory at UIUC, using 3D-printed riverbed models derived from field data