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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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Entanglement distribution is a foundational capability for quantum networks, enabling diverse quantum technologies including—but not limited to—quantum key distribution (QKD). QKD provides
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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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of Computer Science and Technology at the University of Cambridge, UK. This position is part of a broader effort to advance fundamental research in classical and quantum complexity theory. The successful candidate will
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quantum channel, post-quantum mathematics, and traditional classical security, into a single, unified encryption key. Crucially, the system is expected to work with the infrastructure organisations already
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vacuum, charged-particle optics, laser cooling, ion trapping, precision laser spectroscopy, quantum logic and atomic-clock technology. It sits at the interface between atomic physics, quantum technology
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lasers with silicon integrated circuits, fabricated in-house, to make best-in-class switches, attenuators and phase shifters. The technology is very broadband (measured to 250GHz), high power (tested
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-generation quantum technology. Research area and project description: The aim of the project is to exploit electronic properties of nanoscale materials to discover and design new materials for nanoelectronic
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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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Parametric integrators approximate solutions of (high-dimensional) partial differential equations by restricting the numerical approximation to a closed form that nonlinearly depends on, and is