596 computer-security "https:" "https:" "https:" "https:" "https:" "https:" "U.S" Fellowship positions in United Kingdom
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of Manchester and Imperial College. This role involves computational modelling and experimental data analysis, integrating mathematical models of clock neurons and populations with in-vitro and in-vivo
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Computer Science at the University of Nottingham is seeking a talented researcher with skills and experience in soft robotics, specifically in interactive materials to augment robot and human bodies
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Assistance Program For more information check out our benefits page! Your new team - Department of Infectious Diseases The Department of Infectious Diseases at the Peter Doherty Institute conducts impactful
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candidate has either analytical or computational skills (exact diagonalisation or tensor network techniques) and research experience in either many-body quantum physics, statistical mechanics, statistical
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mathematics, statistics, or machine learning, or a closely related discipline • OR near to completion of a PhD • Expert knowledge of Bayesian computation and deep learning methods • Excellent
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computers”(under the UKRI Guarantee scheme). Topics include: - Quantum many-body dynamics - Quantum algorithms - Quantum-enhanced numerical methods - Quantum machine learning - Tensor Networks - Topological
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Closing date: 15th January 2026 Background We are seeking applications for a part time research fellow (70%fte) to work on an NIHR Public Health Research Programme funded project for 12 months. The project
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researcher with a strong interest in optical fibre technology to work on the UK’s Engineering and Physical Sciences Research Council (EPSRC) funded Programme Grant, HiPPo (Smart Fibre optic High-power
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Employer and proud members of the Stonewall Diversity Champions Programme. We are committed to actively exploring flexible working options for each role and have been ranked in the Top 30 family friendly
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for a highly motivated and talented researcher with a strong interest in optical fibre technology to work on the UK’s Engineering and Physical Sciences Research Council (EPSRC) funded Programme Grant