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achieving beam stability with minimal impact on beam lifetime. Detrimental coherent beam instabilities such as, e.g., the slow head-tail or electron cloud instability, are typically mitigated with schemes
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or pathway inference tools Experience working in high-performance computing or cloud environments Interest in developing novel computational or statistical methods for muscle biology Enthusiasm for open
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high-performance computing or cloud environments Interest in developing novel computational or statistical methods for muscle biology Enthusiasm for open science — sharing code, data and reproducible
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frameworks and pipelines Familiarity with single-cell multi-omic data integration and network or pathway inference tools Experience working in high-performance computing or cloud environments Interest in
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on an HPC system or in the commercial computing cloud For further information about this position please contact nternette001@dundee.ac.uk . To find out more about the Group please visit https
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, such as sedimentation, meltwater flow, and vegetation change, into active drivers of adaptive design. This interdisciplinary work combines advanced computational tools, including 4D point cloud modeling and
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of the molecular ISM of galaxies, with a focus on galaxy centres. In particular, this project aims to measure the spatially resolved properties of giant molecular clouds and/or weigh the supermassive black holes
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, such as sedimentation, meltwater flow, and vegetation change, into active drivers of adaptive design. This interdisciplinary work combines advanced computational tools, including 4D point cloud modeling and
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cloud data and 2D floor plans to assess spatial and visual properties of EDs, ensuring data accuracy through ground-truthing. Apply cluster analysis and statistical methods to classify EDs into spatial
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the Biomass Combustion system and RPB-CO2R systems in a unified model. Develop a cloud-based web simulation tool that combines a simplified numerical version of the REUSE system. Key Attributes required: A