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Field
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et al (2015). A hybrid metaheuristic algorithm for the multi-depot covering tour vehicle routing problem. European Journal of Operational Research.
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formulation, which displays striking similarities to that used by the Computational Fluid Dynamics (CFD) community, has inspired the investigators to adopt conventional CFD algorithms in the novel context
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quantitative analysis skills and experience developing algorithms and/or conducting statistical analyses with biological datasets. Background and work knowledge in statistics, algorithms, optimization of novel
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applications for monitoring and managing aquatic environments under study, the Mekong river delta and the Forth river system Develop, test and apply algorithms for the processing and analysis of satellite data
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mix of algorithm engineering and formal methods, alongside more traditional software engineering activities. This project involves developing software which is both mathematically rigorous, and
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or more of: the use of micro/nanofabrication and materials characterization tools; computational multi-physics/electromagnetics modelling and/or the application of machine learning algorithms; experimental
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-resource settings. This project aims to achieve several objectives, including the development of a new AI-algorithm and a paired dataset for comparing how different imaging techniques influence
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, with experience in algorithm development. Confident coding skills and familiarity with modern coding workflows and best practices. Excellent verbal communication skills and the ability to engage
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Desirable criteria Experience of advanced statistical and/or machine learning methods, such as longitudinal analysis methods, latent variables models, clustering algorithms, missing data and clinical trial
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. By integrating cutting-edge multi-agent systems, federated learning, and game theory, this project will develop sophisticated decentralised algorithms that enable autonomous vehicles (AVs