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programming language. Experience of working directly with students, and in university settings would be desirable. You will be required to upload a supporting statement, a CV, and details of two referees as
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programming language. Experience of working directly with students, and in university settings would be desirable. You will be required to upload a supporting statement, a CV, and details of two referees as
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with highly motivated research staff as well as with top national and international partners, and access to state-of-the-art robot platforms. The group is highly international, and the working language
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. Proficiency in the use of statistical programming languages and analysis of large datasets and strong publication records would be essential. Previous experience in atmospheric dynamics and predictability is
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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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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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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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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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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