685 computer-science-quantum-"https:"-"https:"-"https:"-"https:"-"https:" PhD positions in United Kingdom
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The EPSRC Centre for Doctoral Training in Quantum Informatics (QI CDT) invites applications for up to 16 fully funded four-year PhD studentships in Quantum Informatics with Integrated Study for
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2D materials, searching for exotic quantum functionalities to form new sustainable electronics and new types of computing. Tuning nanostructures of these materials with extreme pressure will unlock
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Award Summary 100% fees covered, and a minimum tax-free annual living allowance of £20,780 (2025/26 UKRI rate). Additional project costs will also be provided Overview Edge artificial intelligence (Edge AI) enables deploying AI algorithms and models directly on edge devices. However, AI...
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become accessible experimentally only about twenty years ago, and is now used to realise the first noisy quantum computers. In particular, the main goals are to understand: the non-equilibrium dynamics
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, Computer Science, Natural Sciences, Quantum technologies, although we are open to any enthusiastic applicant with a science-related background. The start date of the studentship is October 2026 (or earlier
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, Computer Science or a closely related field, ideally with a strong focus on quantum computing and numerical simulations. Experience in data-reuploading quantum algorithms, optical quantum computing and quantum
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Department: School of Computer Science Details of Studentship: Fully Funded PhD Studentships Applications are invited from Home and International students for a number of fully-funded PhD
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supervised by: Dr Joschka Roffe, School of Informatics, University of Edinburgh Dr Stergios Koutsioumpas, School of Informatics, University of Edinburgh Dr Vivek Chidambaram, National Quantum Computing Centre
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awareness These funded PhD scholarships are suitable for students with a background in Computer Science, Mathematics, Engineering and Cognitive Science. Students with interests in machine learning, deep
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. The ideal candidate should have background in one of the Machine Learning or Data Science domains with high motivation for upskilling and filling any gaps in their knowledge based on the requirements