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to the development of large-scale quantum communication infrastructure by identifying viable pathways for practical deployment of secure quantum networks. Funding Home students can apply only. Only home tuition fees
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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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computing? Do you enjoy studying complex quantum mechanical systems both from a physical and a mathematical perspective? Are you an innovative and productive team player who enjoys being part of
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computing? Do you enjoy studying complex quantum mechanical systems both from a physical and a mathematical perspective? Are you an innovative and productive team player who enjoys being part of
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Max Planck Institute for Solid State Research, Stuttgart, Hamburg, Halle, Dresden | Dresden, Sachsen | Germany | 3 days ago
for the fast-track option. Your application Are you interested? We invite highly motivated students with a strong commitment to basic science from all over the world to apply to our international program
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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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Come join QuTech and create the Quantum Future! Job description After a successful first hire for this research topic. We are looking for a second candidate to join the Veldhorst group as a PhD
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academic cleanroom in Europe with extensive expertise and specialised facilities for nanofabrication of quantum devices. You will join a diverse and enthusiastic team of academic staff, PhD students and
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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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, or computer science. Core competencies: solid background in quantum many-body physics strong programming skills (Python required, Rust a plus) experience with tensor networks, variational Monte-Carlo, machine learning