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existing data analytics tools will help deploy these technologies in the industry context without the need for big datasets. Predictive Maintenance (PdM) is one of the maintenance strategies that has
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; EPSRC Centre for Doctoral Training in Green Industrial Futures | Edinburgh, Scotland | United Kingdom | 2 months ago
addresses critical analytical challenges in CCUS research and has significant industrial impact but also provides a comprehensive training experience for the PhD researcher, preparing them for a successful
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related discipline. You will have strong experience in one or more of the following areas: electrified powertrains, marine robotics systems, automation, or predictive maintenance using data analytics
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, analytical and computer programming skills. Advantage will be given to applicants with experience in one or more of the following: signal processing, deep learning, acoustics, psychoacoustics, acoustic
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(S.Barak@soton.ac.uk ). Digital and Data Driven Marketing: as one of the top 10 Marketing Departments in the UK, we invite strong PhD proposals in marketing-specific topics, such as Advertising, Branding
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suited to candidates with strong quantitative and analytical skills and a PhD (or near completion) in cancer epidemiology or a related field. Applicants should have experience in applying or developing
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dissertation supervision. For this T&S role, you must have a PhD in a relevant subject (or a PhD near completion – i.e. strictly within three months of submission), and a strong scholarly profile or trajectory
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Duration of Award if full time preferred*: 4 years 1st Supervisor: Dr Tao Lyu 2nd Supervisor: Prof Bruce Jefferson This exciting fully funded PhD, with an enhanced stipend of £25,726 per annum
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digital construction technologies, including VR, IoT, machine learning, and physiological and behavioural data analytics. Experience with wearable sensors & physiological data (e.g., EEG, ECG, eye tracking
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degree or equivalent in a related discipline. This project would suit individuals with academic or industrial experience in electronics, electrical engineering, systems engineering, or AI/data analytics