354 programming-"Multiple"-"U"-"Washington-University-in-St"-"U.S" PhD positions in United Kingdom
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opportunities for embedding storage at multiple points within the HVDC architecture—on the AC side, DC side, or directly within converter submodules. The research will tackle several key technical, economic, and
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potential later start dates.) Supervisors: Professor Gwyneth Davies, Professor Rich Fry (Swansea University) and Professor Jenni Quint (Imperial College, London) Aligned programme of study: PhD in Population
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fees for the period of the relevant programme as outlined in the offer letter (usually three years). CSC will provide living allowances as prescribed by the Chinese Government, and will cover the round
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for the duration of the studentship plus university tuition fees. How to Apply: All applications should be made online via the above ‘Apply’ button. Under Campus, please select ‘Loughborough’ and select Programme
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of childhood cancer death. You will work on the INSTINCT-MB programme, which brings together teams based at Newcastle University, The Institute of Cancer Research and University College London. The programme
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covers tuition fees, a stipend, and RTSG (research training and support grant). Alongside the scientific PhD training, the programme will provide a wide range of training opportunities. DTP Standard
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covers tuition fees, a stipend, and RTSG (research training and support grant). Alongside the scientific PhD training, the programme will provide a wide range of training opportunities. DTP Standard
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Applications are invited to undertake a three-year PhD programme in partnership with industry to address key challenges in manufacturing engineering. The successful candidate will be based
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are invited to undertake a three-year PhD programme in partnership with industry to address key challenges in on-platform manufacturing engineering. The successful candidate will be based at the Rolls-Royce
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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