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requirements of the University. See: www.dcu.ie/registry/making-postgraduate-research-application Important Information: Applications will be deemed ineligible in all cases where they: Do not meet all the entry
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then need to provide the following information in the ‘Further Details’ section: A ‘Personal Statement’ (this is a mandatory field) - upload a document or write a statement directly in to the application
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project meetings / secondments Collaborate with external industrial and academic partners Disseminate research findings through publications and conference presentations For further information please
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that deliver healthier indoor environments, lower carbon emissions, and long-term building performance. By integrating Passive House and EnerPHit principles with real building data, the research will support the
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the Faculty of Engineering, plus those housed in Plant Biosciences at the Sutton Bonnington campus. Data sets will be generated using simulated and experimental data and these will be used to train networks
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for candidates who can demonstrate strong research potential. Suitable backgrounds include, but are not limited to: Human Factors Law (particularly law and technology, medical law, or data governance) Psychology
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: preparing and conducting PhD data collection, teaching, attending conference(s), coursework Semester three: analysing PhD data (possibly publishing), teaching, coursework Semester four: publishing PhD results
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4‑year PhD position in the area of machine learning and computer simulations. The focus of the PhD project will lie on developing machine learning models for clustering, classification, regression and
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page showing the error message or issue, and any details you can, to our Student Support Team . Disclaimer Every effort has been made to ensure the information we have supplied is correct and up to date
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and partner urban sites, the successful candidate will collect and analyse real-world environmental data to evaluate how vegetation interacts with the built environment. You will be supported by a