130 parallel-computing-numerical-methods-"Simons-Foundation" 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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relying on computationally expensive numerical methods. Recent advancements in the application of AI in fire safety has shown its significant potential in improving decision-making, optimizing building
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skills vary widely by age, but can also depend on numerous external factors. Understanding these factors can therefore have important implications for interacting areas that depend on language, especially
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. The research will employ numerical simulation to optimise heat flow within thermal batteries and to design compact heat-exchanger structures that enhance thermal conductivity and temperature uniformity
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minimal NMR data to rapidly predict 3D G-quadruplex DNA/RNA structures – a major leap beyond traditional, time-consuming methods. Work at the intersection of generative AI, molecular dynamics simulations
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system or standalone HP) The project will be supported by researchers and technical staff at CST. To support the project, software such as TRNSYS, MATLAB and Ansys will be used for numerical analysis and
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seeking to support older adults to increase their activity levels, strength, balance and overall health and wellbeing. Methods: This PhD will conduct a mixed-methods programme of research to identify how
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number of these TTR methods exist; tufting, z-pinning, stitching, 3D weaving etc, they are often examined in isolation with “off the shelf” reinforcement materials. This project investigates bio-inspired
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Apply and key information This project is funded by: Department for the Economy (DfE) Summary Many modern technologies — from medical brain-computer interfaces (BCIs) to automated factories — use
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). Interest in interdisciplinary research combining technical methods with real-world economic questions. Essential: Strong quantitative background (computer science, data science, statistics, economics