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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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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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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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experience. Expertise in any of the following topics would be particularly welcome: statistics, data mining, machine learning, stochastic modelling, forecasting, simulation. Applications are by letter of
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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
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of Environmental and Natural Sciences at Bangor University. The post is embedded within an active wastewater research team led by Professor Davey Jones and Dr Luke Hillary. The postholder will mine and integrate
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be based in the Department of Computer Science and the National Centre for Text Mining. Develop biomedical NLP methods for mechanism extraction Design and implement methods for extracting biomedical
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data mining for challenging physics datasets. It will also advance the machine learning and AI methods needed for this work, including the treatment of uncertainty, physical structure, robustness and
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requirements. Maintain accurate records of research activities, data, and outputs in accordance with funder and institutional requirements. Education, Qualifications and Experience Essential PhD in a relevant
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or more of the following methods: agent-based modelling and computer simulation, network analysis, time series analysis, text and data mining Substantive interest in the areas of digital public spheres and