349 machine-learning-phd "The Art Institutes" positions at University of Cambridge in United Kingdom
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research across Cambridge. Machine learning is increasingly at the heart of leveraging enormous and complex astronomical data sets to solve major scientific challenges in our understanding of the Universe
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independent researcher, including through grant writing, independent papers, consulting, trainings. The skills, qualifications and experience required to perform the role are: PhD in Machine Learning, Climate
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analytical skills and substantial experience in machine learning at scale are required. Detailed information on the requirements for the role can be found in the further particulars. The position is for 1 year
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telemetry equipment. They will be responsible for ensuring high quality twins, and will interact with the project team on the development of effective machine-learning models to be deployed within these twin
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Programme for Scientific Discovery (https://acceleratescience.github.io/index.html ) is a high-profile University initiative promoting the use of machine learning (ML) to tackle major scientific challenges
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Applications are invited for a Research Assistant or Research Associate to work on efficient machine-learning systems for earth observation. The post holder will be part of the Computer Architecture
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the Job related to staff position within a Research Infrastructure? No Offer Description Applications are invited for a Research Assistant or Research Associate to work on efficient machine-learning
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We are seeking a highly creative and motivated Postdoctoral Research Assistant/Associate to join the Machine Learning Group in the Department of Engineering, University of Cambridge, UK. This
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linguists and experts in language learning. The PhD studentship is further linked to a part time Research Assistant role for the first two years, supporting the research project of the EF Research Lab
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An exciting opportunity has arisen for someone who is enthusiastic about expanding and developing their existing knowledge of digital tools for learning, in a world-leading higher education