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profound interest in inorganic chemistry, in both experimental and modelling applications. We are looking for candidates who are also interested in the analytical and numerical aspects of the work to support
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performance will be assessed using finite element analysis and experimental work. Additionally, life cycle assessment will be performed to quantify environmental and economic impacts. This project is intended
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, to industrial catalysis and green energy production. This PhD project offers a rare opportunity to explore hydrogen surface collisions at a fundamental, molecular level to gain unprecedented insight into the role
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. This project is intended to perform numerical studies and develop a methodology for the numerical analysis aimed at the effective damping of resonance regimes in bladed disks of gas-turbine engines using
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). Experience in numerical modeling and data analysis. An interest in groundwater contamination, risk assessment, and sustainability. Programming experience (Python, MATLAB, or similar) is desirable but not
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; EPSRC Centre for Doctoral Training in Green Industrial Futures | Bath, England | United Kingdom | 2 months ago
performance. Throughout this PhD, the successful applicant will gain expertise in cutting-edge modelling approaches and experimental techniques including: Thermogravimetric Analysis (TGA) with Mass Spectrometry
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hardware landscape, this PhD project can explore one or more of several directions. The exact design of commercial hardware is a jealously guarded secret, and the numerical behaviour of a specific device has
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Fully Funded PhD Research Studentship tax-free stipend of £20,870 Design, Informatics and Business Fully Funded PhD Research Studentship Project Title: Behaviour-Based Anomaly Detection
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Fully Funded PhD Research Studentship tax-free stipend of £20,870 Design, Informatics and Business Fully Funded PhD Research Studentship Project Title: Autonomous AI-powered red agents for enhanced
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such as landslide movement style, runout, and how landslide hazards evolve over time. This Ph.D. project will leverage the analysis of new time-series data from cloud-based satellite image archives