988 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "University of Waterloo" research jobs in United Kingdom
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will hold a PhD (or close to completion) or possess equivalent research experience in a relevant computational field such as data science, artificial intelligence, machine learning, computer science
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’. The role-holder will work closely with medicinal chemists at University of Oxford and pharmacologists at University of Glasgow, applying virtual screening, machine learning, AI-driven generative chemistry
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to work on the discovery of new superconducting materials with high critical temperatures, using novel methods and concepts such as machine learning and quantum geometry. The project is related to large
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modelling, and machine learning approaches to analyse large-scale datasets, including bulk and single-cell sequencing, gene expression arrays, proteomics, and metabolomics. Working closely with senior
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viewing conditions and across languages. By combining behavioural methods with machine learning, it aims to develop physiologically-based models of lexical colour categorisation. This is a multidisciplinary
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, software engineering, Embedded Systems, Artificial Intelligence / Machine Learning, data science, or closely related disciplines or significant practical/industrial experience. Significant postdoctoral
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publishing work as lead author. Experience with machine learning methods for modelling human learning, such as knowledge tracing and/or experience with conducting research that involves prompting or fine
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As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to be equipped with applied research skill sets
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) in Physics or a related field. Previous experience in cosmological simulations, analysis of cosmic microwave background and/or large-scale structure datasets, machine learning methods applied
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sciences, AI, machine learning or related fields. Strong background and track record in the development of geospatial foundation models from multi-modal Earth Observations is essential as well as strong