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Learning to the problem and also implement at least one classical approach (such as stochastic integer programming) for comparison. The project is a collaboration with Sony who will provide us with real
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integrating diverse data to construct a deep learning-based condition assessment model of underground infrastructure. The condition assessment model is dedicated to bridging underlying correlations between
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programme. The specific collaborative project with industry is to continue a line of research developing machine learning and data analytics techniques to model the dynamic response of specific technical
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social behaviour using zebrafish as a model system. The successful candidate will join a vibrant learning environment working as part of the multidisciplinary Microbiota-Gut-Brain Team within APC
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of the following tasks: - To apply deep-learning (fully-convolutional neural networks) to further refine existing codes for morphological analysis and classification. - To develop finer scale geomorphological
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learning with experience in Large Language models and/or conversational AI (intelligent chat bots) (desirable). • The core team is interdisciplinary therefore the candidate must work well in a team and adapt
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Map (ISSGM v2023). To complete the project we are seeking an experience postdoctoral researcher to address either or all of the following task: - To apply deep-learning (fully-convolutional
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research within the Insight Centre for Data Analytics programme. The specific collaborative project with industry is to continue a line of research developing machine learning and data analytics techniques
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machine learning and modelling of complex datasets requiring integration. S/he will curate, clean and analyse all data, developing appropriate algorithms and pipelines. UCC is an accredited research
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diversity of our student population where people from a wide variety of backgrounds learn from one another, share ideas, and work collaboratively. UCC is committed to being an employer that recognises