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Field
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invites applications from candidates with a robust foundation in data science, modelling, and/or engineering, and a keen interest in deploying data analysis and artificial intelligence (AI) to solve real
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electron microscopy image simulations Development of a machine learning model capable of inferring 3D atomic structure from two-dimensional TEM projection images Application of the new approach
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objective of this research project is to unravel the complex dynamics of iron-dominated, nickel-dominated, and mixed Fe-Ni corrosion products on zircaloy surfaces. By exploring boiling, flow conditions, and
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directly at the site of patient care or field testing, without the need for complex laboratory infrastructure. This demands a detection method that is robust, low-maintenance, and capable of delivering clear
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statistical models (for example principal component analysis) to obtain insights into relationships between physical properties of polysaccharides (composition, molecular weight charge, chain length etcetera
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discover therapeutic targets relevant to Welsh populations. You’ll also help translate your computational insights into lab-based validation using experimental models, paving the way for new diagnostics and
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clearance level. The Engineering Doctorate Researcher will follow the EngD in Model-Based Systems Engineering Programme. They will be based at NPL. Entry requirements: A minimum of an upper-class honours
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learning algorithm to develop an ability to choose what main data pattern/structure to preserve? This PhD project will approach this question by developing modelling strategies and pipelines to enable human
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environmental impacts of digital activities. You will lead projects modelling the energy usage of different computing equipment (personal computers, servers, High-Performance Computing infrastructure
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water basins across HMA. We will simulate future changes in temperature, precipitation, and snowmelt using climate projection models. These projections, combined with hydrological modelling, will allow us