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Field
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attend international and national conferences to present your work and network with other scientists from across the globe. At the end of your PhD, you will be an accomplished and highly-capable scientist
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part of a dynamic, focused and professional study environment and all become valued members of the Cranfield Doctoral Network. This network brings together both research students and staff, providing a
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into full-surface temperature profiles. Key outcomes include defining the required locations and extent of temperature monitoring to enable accurate data conversion. • Creating a practically deployable method
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will then embark on coming up with a suitable design for a generic economic model and construct the model using their software of choice. This new generic model can then be demonstrated by using data
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demonstrable experience in academic writing for publication, e.g. peer reviewed paper(s) and/or report(s) Advanced statistical software skills are desirable, e.g., regression analyses, repeated-measures analysis
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an advantage. The successful applicant will carry out research activities in the domain described earlier and will disseminate research outputs through scientific publications, software development, seminars and
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an Ahmed body will be used as the baseline. Numerical studies will be performed using commercial CFD software. A correlation between experimental and numerical data will be determined. This project
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an international network of colleagues. Entry requirements Applicants should have a minimum equivalent to a UK upper second class degree (2.1) and preferably an MSc in a relevant subject such as Environmental
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discussion regarding the PhD. This is an excellent opportunity for an enthusiastic graduate to build a strong skillset in interdisciplinary research and a collaborative network with both academic and
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motion capture data collection involving patients would be advantageous, as would experience with musculoskeletal modelling software. Candidates with experience in clinical practice relating to human