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conditions. Our work combines traditional statistical methods with advanced artificial intelligence algorithms to identify patterns in disease. We also use qualitative methods to understand lived experiences
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. It will also allow us to build an electronic maternal early warning score, harnessing the power of artificial intelligence to use all the information in the electronic patient record to best identify
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. The successful candidate will become an active member of the Energy, Power and Intelligent Control (EPIC) research centre within the School of Electronics, Electrical Engineering and Computer Science (EEECS
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We are seeking an outstanding, creative researcher with the skills to develop novel, ‘artificially intelligent’ approaches to the application of nanofabrication techniques – see, for example https
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programme in the UK from any other sources. Meet the English language requirement of the UK HEI. Have a background or a proven interest in AI foundations and its application in civil and environmental
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Researcher; Not currently in receipt of financial support or funding towards any other programme in the UK from any other sources; Meet the English language requirement of the UK HEI; Have a background or a
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over India with Machine Learning’ (HEPPI-ML), which is funded through the ‘Weather and Climate Science for Service Partnership ’ (WCSSP) programme. It is also linked to the National Institute for Health
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will primarily support the Head of School (Professor George Panoutsos, Chair in Computational Intelligence) and his research activities in the area of Machine Learning (ML) for Engineering, focusing
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highly motivated and technically proficient Research Fellow in Control and Embedded Systems Engineering to support the development and deployment of intelligent, safety-enhanced BMS technologies within a
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to the development of intelligent design workflows using CFD and data-driven methods to assess and optimise next-generation vessel designs. You will collaborate closely with project partners, applying state-of-the-art