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Start Date: Between 1 August 2026 and 1 July 2027 Introduction: This project fuses machine learning (ML) based inverse design approaches and topology optimisation (TO) to realise multiscale
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microporosity vary across the granites, how is this impacted by mineralogy and macroscopic structures, and how can we scale lab-based measurements of porosity with field observations? The answers
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Number of Opportunities Available 1 fully funded place Department Centre for Doctoral Training in the Modelling of Heterogeneous Materials (HetSys), Department of Physics About the project: Bottom
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the Mauritius parakeet to develop an AI model that can predict the response to viral infection based on genomics data. Moreover, there is the option to conduct fieldwork in Mauritius to gather additional field
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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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strong evidence base on professional cycling road racing trends and identify the key tactical moments that determine race outcomes. This evidence will inform future race strategies and real-time decision
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ecosystem modelling using both field-based and modelled physical and biological data. Collaboration with Centre for the Environment, Fisheries and Aquaculture Science will provide exposure to how science
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PhD Studentship - EASTBIO - Functional Genomics of Host Determinants in Viral Entry and Transmission
work will include mammalian cell culture, CRISPR-based gene editing, and infection models using pseudotyped and replication competent viruses. The student will learn to perform and interpret high-content