653 computer-science-quantum "https:" "https:" "https:" "https:" "https:" "U.S" PhD scholarships in United Kingdom
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(with an average programme mark of no less than 65%) or international equivalent . Candidates should have a strong background in marketing, public management, sociology, or public health. Experience in
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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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Civil Engineering PhD Research Project Directly Funded UK Students Prof R Dwyer-Joyce Application Deadline: 30 August 2026 Details Novel Sealing for High-Pressure H2 and Low-Carbon Storage Technologies
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professional development workshops in areas such as research communication, computing and data science, and professional progression through our Early Career Researcher Institute .Additionally, you will be
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progress from fundamental surface science to the fabrication of intelligent, multiplexed sensor arrays, enabling fast and reliable cardiovascular health monitoring. This exciting 3-year PhD will be conducted
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First or strong Upper Second-class honours degree (2:1 with 65% average), or international equivalent, in Engineering, Computer Science, Physics, Mathematics, or a related discipline, and demonstrate
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PhD Studentship: Building Synthetic Self-Propelled Cells for Bioinspired Motion Are you fascinated by working at the intersection of physics and synthetic biology? This PhD project offers a unique
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training in Government and political science research methods as this will be provided on the programme. Research Proposal The project area is broadly defined, leaving scope for the applicant to develop
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strategic advantages such as discovering new value-creation opportunities. This project will be conducted in collaboration with Circularise, a technology company founded in 2016 that develops blockchain-based
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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