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Vacancies PhD position on the design and fabrication of MEMS drag force-based flow and fluid composition sensors Key takeaways In this project, we will combine well-known thermal flow sensing
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Establishment). Recent work by the group (leading to REF 4* rated outputs and several Keynotes) has contributed to bridging the gap between Computational Solid and Fluid Dynamics, with a unified computational
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for dynamic risk evaluation; (3) the advancement of risk-to-resilience methodologies; and (4) the establishment of digital twin-based resilience frameworks for CI, HTI, and urban environments. The network
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of digital environments utilizing real-time data for dynamic risk evaluation; (3) the advancement of risk-to-resilience methodologies; and (4) the establishment of digital twin-based resilience frameworks
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at the micrometre scale that can propel themselves through fluids, mimicking natural swimming organisms such as bacterial forms. Using biological building blocks found in cells and encapsulating them inside vesicles
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and research cover separation processes, reaction engineering, dynamics and process regulation, process and facility planning, unit operations, heat transmission, fluid mechanics and applied
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Computational Fluid Dynamics (CFD) to diagnose the air quality status of those spaces (presence of pollutants, ventilation, humidity) and to propose measures to improve it. Such measures might imply retrofitting
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and modelling techniques. Real-World Impact: Contribute to transformative technologies in clean energy and carbon capture. Future job opportunities: Digital modelling and computational fluid dynamics
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by using commercial software such as Ansys, Abaqus, SolidWorks, etc. Experience in computational fluid dynamics (CFD) modelling or finite element (FE) modelling; Fundamental knowledge in fluid
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candidate with a strong background in computational fluid dynamics (CFD) and specialized expertise in hemodynamics associated with coronary artery disease (CAD). The ideal candidate will hold a PhD in