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computer science with specialisation in data science, machine learning or deep learning, or in Earth/Environmental Science with experience in applied data science, machine learning or deep learning. You also will
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to recruit a part-time Research Assistant for the project Music Production Style Transfer (ProStyle). The role is to investigate machine learning approaches by which a production style may be learnt from
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machine learning techniques to analyse large data sets held within the network, with the aim of producing novel findings within the field of metabolic ageing. The role will involve engaging with academics
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details and apply Overview About the Role Applications are invited for a Postdoctoral Research Associate with experience in machine and deep learning to work on a research project funded by the Precision
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datasets from national and international cohorts. About You PhD in data science, experience in analysing large multi-modal datasets, machine learning and clinical terminologies About the Institute You will
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at the PDRA level must have a PhD in Computer Science or a related field. Candidates must have substantial knowledge in Deep/Machine Learning, Large Language Models (LLMs) Natural Language Processing and
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Science/Electronic Engineering (or equivalent). Applicants at the PDRA level must have a PhD in Computer Science or related field. Candidates must have substantial knowledge in Deep/Machine Learning, Audio and/or
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details and apply Overview About the Role Applications are invited for a Postdoctoral Research Associate with experience in machine and deep learning to work on a research project funded by the Precision
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of machine learning to assist in the identification and extraction of data from relevant studies, and conducting evidence synthesis work (systematic review, meta-analysis, evidence and gap map, scoping review
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Support the production and distribution of learning materials for all core and elective teaching (including Virtyal/Hybrid requirements) within the department, in line with internal and external regulations