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Job Purpose To contribute to / make a leading contribution to the EPSRC UK Hub for Quantum Enabled Position Navigation and Timing (QEPNT), part of the UK’s flagship National Quantum Technology
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research centre (Hub) funded by EPSRC for a 5-year research programme into Integrated Quantum Networks (IQN). The IQN Hub is supported by an initial £21.8M award from UKRI and additional industrial support
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We are seeking a motivated and Talented experimentalist for a full-time Research Assistant in Quantum Thermodynamics within Professor Ares’ research group at the Department of Engineering Science
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leave, plus 9 buildings closed days (and Christmas Eve when it falls on a weekday) for all full time staff. Use our total rewards calculator: https://www.hw.ac.uk/about/work/total-rewards-calculator.htm
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About us A post-doctoral research associate position is available at the Photonics & Nanotechnology group, Physics Department, King’s College London, funded by the EPSRC Programme Grant New
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project “Spin-orbit coupling and dimensionality at the heart of quantum magnetism of heavy transition metal oxides”. The project is jointly funded between ISIS Facility (led by Dr Devashibhai Adroja) and
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Postdoctoral Researcher in Machine Learning of Isomerization in Porous Molecular Framework Materials
broad range of applications. Computational chemistry and Machine Learning increasingly underlies MFM research to search or screen candidate MFMs prior to synthesis. A major drawback when applying
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) Location: Edinburgh Campus Rewards and Benefits: 33 days annual leave, plus 9 buildings closed days (and Christmas Eve when it falls on a weekday) for all full time staff. Use our total rewards calculator
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"Coupled Magnetic Hybrids for Advanced Quantum Technologies", a collaboration with the City University of Hong Kong (CUHK). The aim of the role is to explore how nanomagnetic elements in proximity structures
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the perspective of numerical analysis and computational mathematics. The overarching aim of the project is to develop new mathematical theory and algorithms to identify, quantify and, where possible, mitigate