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Field
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approaches. Machine Learning in Geotechnical Engineering: Utilising data-driven approaches to model and predict soil-structure interactions or other complex geotechnical problems. Reliability-Based
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of the Grant are:; 1) To apply machine learning algorithms for the diagnosis of faults and malfunctions in photovoltaic plants, using data from SCADA systems combined with synthetic data from digital twins (DT
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, b) computational modelling, or c) machine learning. This is a complex project managing longitudinal data from a range of sources. Therefore, thoroughness and attention to detail while managing
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Python for scientific computing – experience with data analysis and basic signal processing – foundations in machine learning and interest in developing advanced AI models – familiarity with Linux
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, integrating and interpreting them across modalities remains a fundamental challenge. The successful candidate will develop computational and machine-learning frameworks for multimodal neuroscience data
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per year. The successful candidate will be able to teach Introduction to Comparative Politics, in addition to an intermediate-level European politics course and a thematic course in a more specific area
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PhD Research Fellow in ML-assisted reservoir characterization/modelling for CO2 storage (ref 290702)
-build ups in potential multi-site storage licenses. The research will help to suggest best practices for machine learning integration in de-risking CO2 storage sites. We seek a candidate with a strong
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-fellow-in-deep-learning-for-subsurface-imaging Where to apply Website https://www.jobbnorge.no/en/available-jobs/job/290391/postdoctoral-research-fel… Requirements Research FieldComputer scienceEducation
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and to contribute to collaborative papers and grant proposals. Responsibilities • Develop, implement, and evaluate new statistical and machine learning methods aligned with the two themes above. • Lead
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collocates Hawkes (formerly CMIC), UCL’s AI Centre (AIC), and UCL’s Advanced Research Computing Centre (ARC) creating a vibrant hub of data-science researchers with interests from basic machine learning and AI