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to encourage an effective and vibrant research culture, founded upon the diversity of activities and knowledge. A tailored programme of seminars and events, alongside our Doctoral Researchers Core Development
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(Academic Technology Approval Scheme ) clearance certificate prior to obtaining their visa and to study on this programme. How to apply You must apply through the University’s Apply to Newcastle Portal Once
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to obtaining their visa and to study on this programme. How To Apply Please read and complete this document as your Personal statement, and upload this with your application. Applications which do not include
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numerical simulation is desirable. Experience with computational tools such as ANSYS Fluent, STAR-CCM+, or COMSOL Multiphysics would be advantageous. Good oral and written communication skills with
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the average values of the widths and spacings between two adjacent resonances. This energy range is called the “unresolved resonance region” (URR). Current computational methods treat the resonances in the URR
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may require an ATAS (Academic Technology Approval Scheme ) clearance certificate prior to obtaining their visa and to study on this programme. How To Apply Please read and complete this document as
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) clearance certificate prior to obtaining their visa and to study on this programme. How To Apply Please read and complete this document as your Personal statement, and upload this with your application
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, robotics, and machine learning. You will work within a multidisciplinary supervisory team spanning engineering, robotics, and computer science, and collaborate with researchers working on real-world
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(or equivalent international qualification ) with a UK master's degree (with an average programme mark of no less than 65%) or international equivalent . Applicants must meet the minimum English language
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
intelligence, particularly in computer vision and deep learning, offer an opportunity to automate and enhance damage assessment by learning patterns from multimodal data. This research seeks to bridge the gap