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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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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
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The effects of micro-machining operations on structural integrity of biomaterials used in dental applications
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will hold a PhD (or close to completion) or possess equivalent research experience in a relevant computational field such as data science, artificial intelligence, machine learning, computer science