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. The system will leverage cutting-edge techniques in Natural Language Processing (NLP), Machine Learning (ML), and Multimodal Analysis to conduct adaptive interviews, assess candidate responses, and generate
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Laboratory), and will provide experience with new and advanced 3D-printing equipment not available elsewhere. This project is aligned with the “Dialling up Performance for on Demand Manufacturing” Programme
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the PhD in Engineering programme. Make sure to reference the supervisor's name (Dr Farzad Hayati) in your application. Informal enquiries are welcome and should be directed to Dr Farzad Hayati at f.hayati
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Project Overview This PhD project is part of an Innovate UK-funded research programme focused on developing a novel ammonia-fueled engine and generator set (genset) demonstrator for harbour and
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methods experience. Quantitative applicants are expected to have worked with large datasets or equivalent project experiences, and have programming skills such as R coding (preferable) and communication
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skills. Main duties will include: conduct tissue-mechanical and imaging experiments using early avian embryos; acquire and process data; prepare reagents and samples; optimise protocols; program and debug
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researchers at the CCGE, Oregon Health & Science University (OHSU), and the German Cancer Research Centre (DKFZ). This research is part of a Cancer Research UK International Alliance for Cancer Early Detection
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cancer early detection research. The postholder will work closely with researchers from the University of Cambridge, Oregon Health & Science University, the University of Manchester, the German Cancer
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Resilience (WIRe) , a prestigious collaboration between Cranfield University, the University of Sheffield, and Newcastle University. The WIRe programme offers bespoke training that hones both technical and
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Lead Supervisor name: Andrew Callaway, email: acallaway@bournemouth.ac.uk Project description: This PhD programme will determine the most clinically acceptable methods for emergency response teams