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Field
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to train tomorrow’s leaders in earth and environmental science. For further details about the programme please see http://nercgw4plus.ac.uk/ For eligible successful applicants, the studentships comprises
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• Quantitative and computational skills but training will be provided • Interest in Bayesian statistics, stellar evolution, and exoplanet science Keywords Bayesian inference · hierarchical modelling · stellar
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, visions and concerns in innovation. Entry requirements The standard minimum entry requirement is 2:1 in Geography, Sociology, Political Science, Anthropology, Design, Architecture, Engineering, Computer Science
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One fully funded, full-time PhD position to work with Prof. Mahesh Marina in the Networked Systems Research Group at the School of Informatics, University of Edinburgh. The broad aim
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Marine Laboratory. The partnership aims to provide a broad training in earth and environmental sciences, designed to train tomorrow’s leaders in earth and environmental science. For further details about
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to train tomorrow’s leaders in earth and environmental science. For further details about the programme please see http://nercgw4plus.ac.uk/ For eligible successful applicants, the studentships comprises
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PhD programme focused solely on the safety of artificial intelligence (AI). Our vision is to train future leaders with the research expertise and skills to ensure that the benefits of AI systems
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This PhD project is in a competition for a Faculty of Science funded studentship. Funding is available to UK applicants and comprises ‘home’ tuition fees and an annual stipend for 3 years.
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requirements for our PhD programme . Skills in Python, C++ or ROS are preferred. How to apply Applications should be submitted via the Robotics and Autonomous Systems PhD programme page. In place of a research
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to train tomorrow’s leaders in earth and environmental science. For further details about the programme please see http://nercgw4plus.ac.uk/ For eligible successful applicants, the studentships comprises