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Applications are invited for a Research Fellow position on the UKRI-funded Turing AI Fellowship project ‘Event-Centric Framework for Natural Language Understanding’ led by Prof. Yulan He. The 5-year project aims
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) information-theoretic active learning, and c) capturing uncertainty in deep learning models (including large language models). The successful postholder will hold or be close to the completion of a PhD/DPhil in
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of Romance Studies offers Bachelor’s, Master’s and PhD degree programs in five Romance languages and teacher-training courses for secondary schools in three languages (French, Italian and Spanish
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to the EPSRC programme grant "Terahertz frequency devices and systems for ultrahigh capacity wireless communications (TERACOM)" (teracom.uk), EP/W028921/1. This is a collaborative project involving the
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of Edinburgh and Glasgow, with expertise across computer science, wearable computing, AI and criminology. Our programme of research utilises both experimental and literature-based approaches to explore
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team working at the forefront of public service reform, in close collaboration with academic, government, and civil society partners. The successful candidate will contribute to a programme exploring how
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/statistical modelling, numerical/data analysis, and programming using Python or other languages a motivation to engage in systems approaches to understand complex risks Contact details for advert Contact Name
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applications (e.g. natural language processing, multivariate time-series data), to develop systems that improve the efficacy of machine learning-based technologies for healthcare applications. You must hold a
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Participate in meetings to discuss the AQPU plan together with the team Help your peers in solving their challenges in reaching the milestones including the supervision of BSc theses and possibly of PhD and MSc
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into real-world settings. You will be responsible for developing machine learning and AI algorithms for a range of data and applications (e.g. natural language processing, multivariate time-series data