133 machine-learning-"University-of-California,-Santa-Cruz" positions at University of London
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Overview About the Role Applications are invited for a motivated and committed Machine Learning Engineer. The successful candidate will contribute to Queen Mary’s national reputation for research by planning
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PGT programmes. About You The successful candidate will have experience of using virtual learning environments, knowledge of learning technologies and skilled at working with computer-based record
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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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View All Vacancies Centre for Excellence in Learning and Teaching Salary: £43,947 to £49,908 per annum, inclusive. Closing Date: Sunday 14 April 2024 Reference: DOE-CELT-2024-01 The London School
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effects T cell ageing. This position would particularly suit a researcher with an interest in the application of complex bioinformatic analysis and machine learning to create a model of metabolic T cell
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computing, AI, biomedical engineering or signal processing) or a higher degree (e.g. MSc) with substantial experience in multimodal machine learning with appropriate track record. Excellent programming skills
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health is essential. Knowledge and application of machine learning, Chat GPT or other AI software would be desirable. Further particulars are included in the job description. The post is full-time 35 hours
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Telescope. This research may involve the analysis of large datasets, the generation of new simulations and the utilisation of Machine Learning techniques. The PDRA will be expected to hold a PhD in
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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