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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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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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use of machine learning methods to process complex data sets. The focus is on techniques such as ultrasound, radar, computed tomography, acoustic emission analysis, and infrared thermography. Industry
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laboratory techniques helpful, but not required. Exposure to applicable computer technologies, including specific software applications (Microsoft Office/365), may be required. Strong communication skills
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groups. Applicants with disabilities will be given preference in case of equal qualifications. More information about our research and team can be found here: www.lse.ls.tum.de/fmp. Application – Please
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Collaborate with CCY researchers on ongoing projects and contribute to the development of new research initiatives Contribute to data analysis and data management Contribute to national and internationals
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academic approval, and the candidate will be enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme