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Field
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, you will explore water-gas shift chemistry to tailor sustainable carbon dioxide and hydrogen concentrations as the first step to produce sustainable fuels. During the project you will design manufacture
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but not essential. A strong background in materials science and/or modelling is essential. Experience in machine learning, computer vision, and computer programming is desirable. In addition
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. Development of DT information modelling, data fusion, and forecasting guidelines and standards, and technology maturity benchmarks to derive cloud platform maturity level standards. Lead on the development
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, to discuss the project or if you have any questions. Entry requirements: Applicants should have, or expect to achieve, at least a 2:1 bachelor’s degree (or equivalent) in biomechanics, sport science
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and/or Python, is highly desirable. Experience of collecting neuroimaging and/or wearables data from infants/children is also desirable. The project will be based at the Institute for the Science of
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biology, chemistry, psychology and social science, facilitating knowledge discovery. The intuitively uninterpretable high-dimensional data and network data become visually scrutable upon being mapped into 2
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ballot may leak the voter’s preferences if published publicly in plaintext, as the ranking order can reveal detailed information about the voter’s identity. Therefore encryption is necessary to hide
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, interpretable models from experimental and operational data. The core goal is to balance model accuracy with computational efficiency, while meeting the needs of experimental validation. The framework will
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of collecting neuroimaging and/or wearables data from infants/children is also desirable. The project will be based at the Institute for the Science of Early Years (www.isey.org ) in London, UK. Supervision will
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team of researchers using operational and information-theoretic tools to gain insights into quantum foundations, causality, and space-time physics. We are convinced that further progress on open problems