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for mining, classifying, and forecasting from heterogeneous data sources Spatial-temporal statistics/modelling from heterogeneous data (Bayesian hierarchical models, autoregressive models, random fields
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metals have high production costs because they are low in abundance (requiring high volumes of ore to be mined, often in regions of political instability) and typically come with extensive purification
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About us The Department of Informatics is looking to recruit a Postdoctoral Research Associate to work on data mining, in the context of a project funded by Leverhulme Trust, in the Department
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infrastructure over time, under different scenarios. Expected Results: 1) Development of geometric deep learning, time-series data mining, and agent-based approaches incorporating microbial information for DWDSs
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approaches and technologies (including text mining, coding, VR and data visualisation) across all subjects. This is an exciting opportunity to contribute to the University’s Education and Research strategies
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of the Department’s activities in the field of Business Analytics. We welcome discussions with prospective candidates who have interests in specified areas of business analytics such as data mining, machine learning
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at least one of the following (Autonomic Intelligent Systems, Data Mining, Machine Learning, Semantic Web, Software Development, Web & Network Services) To apply for this role, please click on the 'Apply
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process mining, which revolves around the data-driven analysis of organizational processes. We offer an excellent and international working environment. As a member of the team, you contribute directly to
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; ore mineralogy and geometallurgy; or mining geology. The Department of Earth and Environmental Sciences is a lively and dynamic community that aims to promote sustainability through education
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Engineering / Mining Engineering: Emerging and disruptive construction technologies / High-performance construction materials with reduced embodied carbon / Tunnel engineering with expertise in design