650 computer-science-quantum "https:" "https:" "https:" "https:" "https:" "U.S" PhD scholarships in United Kingdom
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ready for further downstream magnet recovery processes. Who we are looking for A first or upper-second-class degree in an appropriate discipline such as, robotics, mechatronics, computer science
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The PhD (Finance) program at Durham University provides rigorous research training that prepares students to become leading experts in their chosen field. Faculty members in the Finance Department
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background in engineering (electrical/mechanical/electrochemical), achieving a 1st or 2(1) in their undergraduate studies with a focus on experimental activities, engineering design and numerical analysis. A
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Engineering Department Location: Newport, Shropshire TF10 8NB Post Type: Full Time Contract Type: Fixed Term - Studentship funded for 3 years Closing Date: 23.59 hours GMT on Sunday 01 March 2026
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sub-skills. International applicants may require an ATAS (Academic Technology Approval Scheme ) clearance certificate prior to obtaining their visa and to study on this programme. How To Apply You must
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computer science, mechanical engineering, or aerospace engineering. You should have programming experience applied to physics/engineering problems and/or experience with machine learning and ML. The University
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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 requirements. Further details
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requirements At least a 2:1 honours degree (or equivalent international qualification ) with a UK master's degree (with an average programme mark of no less than 65%) or international equivalent . Applicants
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. Specific requirements of the candidate The successful applicant is expected to have: An honours degree at first or upper second-class level in Cyber Security, Artificial Intelligence, Computer Science
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in recycling, bioremediation and green chemistry. Candidate enzymes are mechanistically investigated, structurally characterised and subsequently improved by directed evolution. Ultrahigh-throughput