251 network-coding-"Chung-Ang-University"-"Chung-Ang-University" PhD positions in United Kingdom
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within the Faculty of Engineering have access to bespoke courses developed for Engineering PGRs. including sessions on paper writing, networking and career development after the PhD. The Faculty has
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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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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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members of the Business Disability Forum and Stonewall University Champions Programme. Cranfield Doctoral Network Research students at Cranfield benefit from being part of a dynamic, focused and
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sold network with aerospace sector which help the students in the result discussions This is a self-funded PhD open to UK, EU and international applicants. Research carried out during this PhD project
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to industrial clients such as Boeing, BAE Systems, Rolls-Royce, Meggitt, Thales, MOD, Bombardier, QinetiQ, Thales, Network Rail, Schlumberger and Alstom. Entry requirements A minimum of a 2:1 first degree in a
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). PROJECT The net zero and sustainability targets as well as export cost means that there is increased need to rely on new class of alloys with higher recycle content must be developed for both high strength
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upper second-class honours degree (or equivalent) in Engineering, Physics, or Applied Mathematics. Experience in coding and CFD is advantageous but not mandatory—an eagerness to learn and innovate is key
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Bradford Teaching Hospitals NHS Foundation Trust, where you will get to network with researchers from the NIHR Yorkshire & Humber Patient Safety Research Collaboration and the NIHR Yorkshire & Humber Applied
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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