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computational models, which may incorporate machine learning, language processing, information filtering, and network model methodologies. 4. Produce and share code in collaborative environments within the group
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. 1. exploring how probabilistic or machine learning methods could be employed to improve the inputs into large-scale agent-based simulations of urban mobility patterns, allowing for more realistic
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great broad-based research-intensive universities. Applications for the post are welcome in the general areas of Human-Computer Interaction (HCI), which complement existing strengths in the Glasgow
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University in St Louis and Nationwide Children’s Hospital in Ohio and is funded by the US National Institutes of Health. This is a fantastic opportunity for a candidate to develop new machine learning and
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quantitative methods, social network analysis, text analysis, Bayesian modelling, longitudinal analysis, causal inference, agent-based modelling, Machine Learning, or similar. Skills Essential: C1 Excellent
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to the field of research (e.g., 3D dynamic computer graphics, Machine Learning, AI, cognitive science, signal processing, computational modelling). C3 Knowledge of project-specific technical models, equipment
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wider subject area or subject specialism A3 Knowledge and hands on experience of radar sensing and machine learning Desirable: B1 An awarded (or recently submitted or near completion) PhD in subject
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Job Purpose To make a leading contribution to a project Machine Learning Accelerated TCAD Simulations working with Prof. Vihar Georgiev. The successful candidate will also be expected to contribute
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) or equivalent in a relevant subject or a cognate discipline with specialist theoretical and practical knowledge of machine learning/AI and cloud-based computing/visualisation and its use in medical diagnostic
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leveraging recent advances made in multiscale mechanics and machine learning. The candidates should have a PhD, or have equivalent experience, in Mechanical, Civil, Chemical, Material Engineering, Physics