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Northeastern University London Fully Funded PhD Scholarship in Computer Science Reliable Quantum Statistics Northeastern University London > Computing, Mathematics, Engineering & Natural Sciences
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have any questions, please contact the principal supervisor, Dr Masoud Ghalaii ([email protected] ). To apply you will need to complete the online application form for a full time PhD in Computing
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Application deadline: 01/12/2026 Research theme: Quantum communication, condensed matter, quantum optics How to apply: https://uom.link/pgr-apply-2425 This 3.5 year PhD project is fully funded
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students and to engage with the broader quantum computing and theoretical computer science communities at Cambridge. Essentia criteria Successful candidates will hold (or be close to completing) a PhD in
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Quantum computers are on the horizon that could break the encryption protecting our banks, hospitals, and national infrastructure. This fully funded, part-time PhD studentship offers the chance to
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working in the group of Professor Martin Cryan and will be a member of the Photonics and Quantum Research group which comprises around 50 Academics, Post-doctoral researchers and PhD students with access
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4-year PhD fellowship in the Research Programme - Deep Learning-Accelerated Crystallography Pipeline
qualification equivalent to a Master’s degree in Chemistry, Mathematics or Computer Science by the start of the PhD; A curious mind-set and strong background in quantum crystallography and its underlying
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heterostructures for functional quantum devices. The candidate will receive a broad training on computational materials modelling and gain experience with cutting edge quantum transport simulation methods, conduct a
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identified by, a set of parameters. Such methods are a popular choice in quantum dynamics, where the wavefunctions of many-body systems are approximated by multiple Gaussians. The methodology of interest
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for device functionality and reduced electrical current requirements, making them highly promising for energy efficient computing and storage technologies. This PhD project will provide novel insights