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’. Use ‘Course Search’ to identify your programme of study: · search for the ‘Course Title’ using the programme code: 8040F · Research Area: Civil Engineering · select ‘PhD Civil
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An exciting opportunity has arisen for two Research Assistants (RAs) within the Institute of Mental Health. The RAs will be working on the ESRC/NIHR funded DETERMIND programme (www.determind.org.uk
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work on the INSTINCT-MB programme, which brings together teams based at Newcastle University, The Institute of Cancer Research and University College London. The programme will generate a wide range of
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Cranfield is an exclusively postgraduate university that is a global leader for transformational research and education in technology and management. Research Excellence Framework 2014 (REF) has recognised 81% of Cranfield’s research as world leading or internationally excellent in its quality....
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The research in this doctoral opportunity will investigate the relationship between material elastic and thermal properties by using high resolution digital imaging under dynamic loads. Digital image correlation is an effective tool to characterize material properties. The analysis of the images...
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If a member of staff would like to carry out a part-time (PT) PhD at HAU the following conditions apply. Staff wishing to carry out a PT PhD at HAU should follow the following procedure
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Research Assistant/Associate to undertake work as part of our NU Solve programme. Newcastle University Solve (NU Solve) in the School of Mathematics, Statistics & Physics (MSP) has a track record of
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An exciting opportunity has arisen for two Research Assistants (RAs) within the Institute of Mental Health. The RAs will be working on the ESRC/NIHR funded DETERMIND programme (www.determind.org.uk
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problem-solving skills and deep expertise in the development of complex computational models. Candidates who have not yet acquired their PhD would be appointed at the Research Assistant level. The
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& robust control, and learning for dynamics & control. The main task of the PhD student will be to develop sound data-driven methodologies for learning control policies with provable guarantees