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interconnected computing nodes, actuators and sensors, communicating over networks, to achieve complex functionalities, at both slow and fast timeframes, and at different safety criticalities. Future connectivity
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a mixture of experimental and computation work. A current key focus of the group is development of new multiscale modelling approaches, coupled with data driven modelling techniques, to support
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Overview Are you experienced in using applied maths to model an acoustic problem and analyse data? Do you enjoy working collaboratively? This role offers an exciting opportunity to apply your
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Overview Accurate modelling of the solar atmosphere is essential for understanding the energy flow and accumulation that underpin the heating of the solar chromosphere and corona, and for uncovering
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personal development budget which can be used for relevant professional development activities including a residential programme at Ashorne Hill to further develop your professional skills and network. You
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driving through deep reinforcement learning. Computing demands can grow rapidly with such models, so a significant aspect of the research is in formulating the problem in a tractable form, and application
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different supernovae models. In addition to these analysis topics, students have the opportunity to engage with the scientific programme of work that the Sheffield group is pursuing for both the Super-K and
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PhD at the Forefront of Computational Solid Mechanics and Machine Learning School of Mechanical, Aerospace and Civil Engineering PhD Research Project Self Funded Dr J L Curiel Sosa Application
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lead and perform research in these areas, who will have practical experience of blast experimentation, underwater blast loading, and demonstrable computational modelling experience in a relevant area
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performance. Research in the group is a mixture of experimental and computation work. A current key focus of the group is development of new multiscale modelling approaches, coupled with data driven modelling