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Appropriate computational skills and knowledge of programming languages (Python, C++, etc.) Experience with Machine and Deep Learning models and software (Keras, Scikit-Learn, Convolutional Neural Networks, etc
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” highly flexible components and ensure their energy harvesting capabilities. This project will contribute to ambitious plans for SBSP as a vital part of the future Net Zero landscape. Recent advances in
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discussion regarding the PhD. This is an excellent opportunity for an enthusiastic graduate to build a strong skillset in interdisciplinary research and a collaborative network with both academic and
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wealth inequality, and how their career paths, values, and social networks maintain the status quo. As a PhD student on this programme, you’ll play a key role in generating new insights that could help
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alongside numerical simulations relying on high-performance computing and reduced order modelling. We aim to gain new insights about the physical coherent structures which are most relevant to viscoelastic
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EPSRC iCASE PhD studentship with SLB - Computational modelling of advanced geothermal systems School of Mechanical, Aerospace and Civil Engineering PhD Research Project Directly Funded UK Students
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+4 - covering a full postgraduate research programme Please note that existing postgraduate research students cannot be considered for this funding. Tenable period 4 years full-time or 8 years part
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within the Centre for Digital Innovations in Health & Social Care, you will join an active research centre and will be collaborating with researchers as part of a programme of research concerned with
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increasingly important and pressing due to the rapid growth of offshore renewable energy as a critical part of the UK’s ambitious plan to achieve net-zero greenhouse gas emissions by 2050. These extreme waves
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nationals only) and research costs) three-year full-time PhD available to start on the 1st October 2025. The overall theme of this PhD programme is improving clinical assessment and research access