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programmes that are constantly renewed in response to issues in society. Our faculty is large enough to make a difference nationally and internationally, yet small enough to offer personalised education. This
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are expected to work as a close-knit team together with three PhD students to create a mutually supportive research environment. Candidates must be enthusiastic about building and working in a large
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researchers from around the world are tackling global issues and making a difference to people's lives. We believe that inspiring our people to do outstanding things at Durham enables Durham people to do
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sensing provides large-scale and consistent observations, in-situ data collection remains a vital component for ground-truthing, model calibration, and validation of automated monitoring. However
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roadmaps. the state-of-the-art methodologies and technologies from different stakeholders in the field of digital twin spacecraft, in particular ESA/ESTEC, ESA/ESOC and the large space integrators
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if there are special grounds, for example, different types of statutory leave of absence. Applicants who are close to finishing a PhD are also encouraged to apply. Further information The position is fully funded by
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two PhD students in the groups, and your newly developed tools will support the analysis and interpretation of their data. You will interact strongly with several international collaborators, both
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test planning, instrumentation (e.g., strain gauges, LVDTs, DIC), execution of large-scale tests, and data analysis. Solid understanding of structural behavior, failure mechanisms, and durability issues
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. Required Qualifications: Doctoral degree (PhD) conferred by start date Demonstrated experience with analysis of large health databases Training and experience in machine learning and deep learning methods