404 machine-learning-phd-"The-Art-Institutes" positions at University of Cambridge in United Kingdom
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them to the electric ducted fan design. First, there are many Machine Learning algorithms available and there are several cases of successful adoption of these into aerospace engineering. However, they
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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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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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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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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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The Blended Learning Service works collaboratively across the University with academics and professional staff in support of teaching, learning, and assessment to further institutional developments