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Simulation of particle physics experiments on graphical processing units School of Mathematical and Physical Sciences PhD Research Project Self Funded Prof D Costanzo Application Deadline: Applications accepted all year round Details In this project you will combine state of the art software...
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facing the UK’s programme of remediation and restoration of the Sellafield site, expected to be complete in the next century. The PUMaS hub will support ~20 PhD students along with research staff, creating
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Overview We are seeking a highly motivated research associate to lead a collaborative project between Johnson Matthey PLC and The University of Sheffield. This role offers a unique opportunity to apply your mathematical modelling, coding, and ultrasound instrumentation expertise to develop and...
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. This paves the way for the application of MPC to large-scale systems, since the computational bottleneck is removed. The basic challenge is how to coordinate the distributed decision making of agents so that
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programme grant on hybrid energy storage systems for grid-independent EV charging stations and there will be significant opportunities for the successful candidate to interact with the interdisciplinary team
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will work with the programme leader, academics and practice partners to support students and will attend meetings across the partnership locations. They will be expected to contribute towards development
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. withdrawals, change of programme, leave of absence). Assisting with other activities associated with the change of status process, e.g. reporting to the Student Loans Company, sending standard confirmation
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-01126-2 Purshouse RC, Deb K, Mansor MM, Mostaghim S, Wang, R. A review of hybrid evolutionary multiple criteria decision making methods. Proceedings of the 2014 IEEE Congress on Evolutionary Computation
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AMRC marketing teams Programme Administration & Support Be the point of contact for students and supervisors, and provide guidance and support on matters related to the PhD and EngD programmes Support
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Early-stage failure prediction in fusion materials using machine learning