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Field
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of Computational Linguistics/Natural Language Processing (NLP), Computational Psycholinguistics and Language Acquisition. The PhD Project Despite the impressive advances made possible by neural networks, current NLP
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-effective alternative to the UK-CCI by applying machine learning and NLP techniques to articles published in leading UK newspapers. The linguistic analysis of text in Economics and Finance has become very
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. Arianna Bisazza. This is an interdisciplinary project at the intersection of Computational Linguistics/Natural Language Processing (NLP), Computational Psycholinguistics and Language Acquisition. The PhD
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of the virtual assistant at multi-tasking experimental workstations, specifically at the X-ray scattering beamline CMS (Complex Materials Scattering). You will research frontier natural language processing (NLP
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activity logs Coordinating, guiding and monitoring junior developers and analysts Collaborating with NLP experts to improve activity designs Conduct user experiments with students remotely and in-person
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with large amounts of data. Experience working with applications of RPA, NLP techniques and machine learning would be advantageous. Strong interest in the application of data science and generative AI
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Grant and coordinated by Principal Investigator (PI) dr. Arianna Bisazza. This is an interdisciplinary project at the intersection of Computational Linguistics/Natural Language Processing (NLP
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in one or more domains, such as classification, Natural Language Processing (NLP), computer vision, recommendation systems, and forecasting. Experience translating business requirements to technical
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scientific programming and conceptual understanding, 2) design of assignments, best practices, and guidelines for use of generative AI in science teaching and learning, and 3) exploration of how NLP methods
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FIZ Karlsruhe – Leibniz-Institut für Informationsinfrastruktur | Eggenstein Leopoldshafen, Baden W rttemberg | Germany | 17 days ago
, aggregation, linking and retrieval of comprehensive heterogeneous and distributed data sources. To this end, both statistical and linguistic analysis methods (NLP) as well as machine learning in combination