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and Prof Paul Shearing. The post is funded through a strategic research partnership and is fixed term for up to 2 years. To support the programme, the post holder will be required to carry out research
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other partners in the project. About you You should possess a PhD/DPhil in Engineering, Computer Science or other related field, (with the possibility to underfill at Grade 6 (£34,982 - £40,855 p.a
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possess a PhD/DPhil in Engineering, Computer Science or other related field, (with the possibility to underfill at Grade 6 (£34,982 - £40,855 p.a.) if candidate holds a relevant degree and is working on PhD
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level training in a relevant field. For Appointment at Grade 7: A2. Normally Scottish Credit and Qualification Framework level 12 (PhD) in a relevant subject such as computer science, statistics, machine
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may be possible, please contact Professor Kamalan Jeevaratnam once the deadline passes. You will need to meet the minimum entry requirements for our PhD programme . This is an interdisciplinary project
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a closely related field. A strong background in quantum mechanics, solid-state physics, and computational modeling. Previous experience with density functional theory or many-body physics (beneficial
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace - In Partnership with Rolls-Royce PhD
Overview: Cranfield University invites applications for a fully funded 3-year PhD, supported by the EPSRC DTP and Rolls-Royce. This studentship covers tuition, a tax-free stipend, funding
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-temporally cooperate to result in an emergent macroscopic flow. Besides the immediate applications of the work to soft matter physics, and potentially also to the fracture mechanics of hard materials, yielding
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their practical deployment. The Project: This PhD will develop the science and engineering required to overcome these bottlenecks, with the following objectives: • Uncover the mechanisms driving enhanced hydrogen
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synergies between methods and ideas of modern machine learning and of statistical mechanics for the study of stochastic dynamics with application to the analysis of time series. In particular, the project