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Field
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-rounded academic background ◾Demonstrated ability to develop precision mechatronics system and algorithms ◾Ability to develop kinematic and/or dynamic analysis of mechanical/robotic systems ◾Ability
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powerful framework for decentralised machine learning. FL enables multiple entities to collaboratively train a global machine learning model without sharing their private data, thus enhancing privacy
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The development of electric vertical take-off and landing (eVTOL) vehicles is one of the best solutions for solving transportation problems such as air pollution, road congestion, and long commute
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, government, and wider society. In the REF2021 review of UK university research, 88% of Cranfield’s research was rated as ‘world-leading’ or ‘internationally excellent’. This project will develop a robust
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meetings. Project Background This project directly supports QCI3's vision of integrated and interconnected implementations by developing essential benchmarking tools that bridge across all three themes
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We are a world class research-intensive university. We deliver teaching and learning of the highest quality. We play a leading role in economic, social and cultural development of the North East of
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the MRC Centre for Neurodevelopmental Disorders. At the Centre for Developmental Neurobiology (CDN), we investigate the mechanisms governing the formation of the brain during embryonic development and in
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to work with an international team on developing cutting-edge novel demographic, statistical and computational methods in estimating, modelling and forecasting measures of health, well-being, and human
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this issue and we could use obtain data-driven models using machine learning algorithms such as artificial neural networks, reinforcement learning, and deep learning. A typical caveat of data-driven modelling
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very well the behaviour of these cryogenic hydrogen pumps, in order to master their integration into the hydrogen system. The primary objective of this research in collaboration with Airbus is to develop