599 computer "https:" "https:" "https:" "https:" "Univ" PhD positions in United Kingdom
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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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upper second-class undergraduate degree in any of Engineering, Materials Science, Computer Science, Physics, Mathematics. Excellent English written and spoken communication skills. It is desirable
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, the School has a vibrant research culture in which its established doctoral programme plays a vital role. It is home to the Centre for the Study of Democracy, the Centre for Social Justice Research, and the
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Once you have discussed your project with a prospective supervisor, you will need to make an application for a place on a postgraduate research programme. Please browse our course listings for a
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undergraduate degree (or international equivalent) in Engineering, Industrial Engineering, Manufacturing Engineering, Systems Engineering, Operations Management, Computer Science, or a related field. A master's
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. This PhD project will address these critical gaps through an ambitious translational research programme combining human studies with cutting-edge laboratory science. The student will design and lead a
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this programme. How to apply You must apply through the University’s Apply to Newcastle Portal In ‘Course choice’ tab, put ‘Postgraduate Research’ in 'Type of Study', ‘Full Time’ in ‘Mode of Study’, ‘2026’ in
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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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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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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