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information/data from one structure can be used to manage similar structures from the same population. New machine learning, sensing and digital twin technologies will be developed with the aim of driving new
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lifecycle. You’ll have a particular focus on employee relations, learning and development, and using data to drive continuous improvement. Your support will empower managers to lead confidently and create
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Computer Science, Chemistry, Chemical Engineering, Physics, or Materials Science. You will develop optimisation and machine-learning algorithms for human- and literature-informed discovery of new materials
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Development and Validation of a Multimodal Wearable Headband for Objective Bruxism Monitoring Using Machine Learning (S3.5-DEN-Boissonade)
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science and applications. This project aims to develop the required formalism using modern probabilistic and machine-learning approaches, reformulating the problem in terms of conditional probabilities
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(Research Assistant) or PhD degree (Research Associate) in computer science or a related area or equivalent experience. Familiarity with standard machine learning libraries/data analysis, specifically as
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reinforcing our Safer Recruitment commitment. We're very proud to be a signatory of the Armed Forces Covenant . an accredited Disability Confident Leader ; autism friendly university , committed to building
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Recruitment commitment. We're very proud to be a signatory of the Armed Forces Covenant . an accredited Disability Confident Leader ; autism friendly university , committed to building disability confidence and
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on basic laparoscopic surgery tasks, using data collected under varying network conditions and applying machine learning and time-series modelling to predict delay. The models will be integrated into a real
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engineering Antennas and propagation Electromagnetics Radar and sensing Communications systems Spectrum, interference and regulation Embed RF learning within NMITE’s challenge-based pedagogy Lead programme