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Field
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in experimental physics and superconducting device development, with a focus on advancing multipixel single-photon camera technology and multiplexed readout for quantum information science applications
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Position Description The position The Algebraic Combinatorics and Fundamental Physics Unit, led by Matteo Parisi, investigates new combinatorial and geometric structures underlying quantum field
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Computational Chemistry, Materials Science, or a related field. Strong background in computational chemistry techniques, including molecular dynamics, quantum mechanical simulations, and machine learning
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for Energy, Environment and Sustainability *Optical Materials and Light Matter Interactions *Quantum Materials Science Qualifications A PhD in Materials Science, Optics, Physics, Chemistry, Electrical
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scientist to carry out a research programme focused on developing novel ultrafast light-source technologies in gas-filled hollow-core anti-resonant fibres. The role will involve working in close collaboration
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strong background in both materials physics and computation to join our Quantum Materials team. We seek candidates who are interested in developing cutting-edge tools for analysis of comprehensive single
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Position Title: Postdoctoral Researcher in Machine Learning and Computational Chemistry Appointment Type: Post Doc/Trainee Job Description: Summary of Duties and Responsibilities: The Postdoctoral
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funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description A central pillar of the activity
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include quantum phases of matter, quantum computing, quantum error correction, non-equilibrium physics, critical phenomena, open quantum systems, and quantum simulation. This is a full-time position for
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of symmetry breaking, domain dynamics, and light–matter interactions with the development of concepts relevant to next-generation information technologies, including neuromorphic and low-power computing