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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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and advanced manufacturing, Brainport is a place where technology serves people and society. Learn more about the Brainport region here . The mission of the Department of Electrical Engineering is to
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Building a quantum computer that can solve real-world problems will require the integration of many highly coherent qubits. Hole-spin qubits in planar germanium quantum wells are among the most
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, including cutting edge quantum physics and chemistry, material science, nanotechnology, biochemistry, cell biology, or medical research. The SNI PhD programme includes multiple social events, trainings in
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Max Planck Institute for Solid State Research, Stuttgart, Hamburg, Halle, Dresden | Dresden, Sachsen | Germany | about 2 hours ago
) - all of them world-leading institutions in their respective fields - bring together their expertise in the research on quantum materials and thus offer a truly unique graduate program in this intriguing
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physics of our universe at the nanoscale: from atoms and fundamental particles from a century ago, to the quantum sensors and computers of today, quantum mechanics governs how these microscopic objects and
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potential for covering the growing need for high-precision sensors, both for basic science and for industrial applications. State-of-the-art quantum sensing methods rely on spin defects hosted in three
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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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networks and quantum circuits using techniques from (formal) computer science. You will work closely with this growing team, where most members, including the first PhD candidates who joined in September
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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