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spaces and habits for them. This is a highly interdisciplinary project that combines computational modelling and behavioural science. The first part will be based on the use of state-of-the-art
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(or equivalent) in a biomedical science. Experience in neuroscience and/or immunology is desirable. Project key words Retinal imaging, data-analytics, computer vision, big data Funding The studentship, funded by
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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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-oriented, especially with regard to data management and writing Willingness to work as part of an interdisicplinary team across science and social science Excellent communication and organization skills
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project funded by the Leverhulme Trust. Description below: The density of information content in screen media – i.e., the light, volume and pitch changes from which we extract meaning – has increased
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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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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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, 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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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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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