704 high-performance-quantum-computing-"Multiple" Fellowship positions in United Kingdom
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Technologies, Physics or a closely related field (e.g. Electronic / Electrical Engineering, Computer Science). They should have a track record of high-level research in THz systems, quantum technologies
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responsibilities will include: Establish and Lead Innovative Research: Develop a research programme addressing the Centre's strategic areas in cancer genome discovery, diagnostics, and translation. Foster
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of the literature relating to ‘Blairism’ and to the study of legacy effects in policy analyses A high level of competency with time series modelling OR age-period- cohort modelling OR structural equation modelling A
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be close to completing a PhD in computer science, mathematics, or a related area with a topic close to type theory or constructive mathematics. Expertise can be evidenced through publications
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development of the National Facility for Ultra-High Field (11.7T) human MRI/S at the University of Nottingham. We are looking to recruit MR physicists and biomedical engineers, or equivalent, enthusiastic
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This is a theoretical/computational postdoctoral position for the prediction and development of point defects in two-dimensional materials for applications in quantum technologies. Project
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This is a theoretical/computational postdoctoral position for the prediction and development of point defects in two-dimensional materials for applications in quantum technologies. Project
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wavefunction calculations on high-performance computing clusters. You may also: Possess a PhD (or near completion) in Theoretical Quantum Chemistry or a related discipline. Have experience in developing and/or
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algorithmic foundations of quantum adversarial machine learning, an emerging field at the intersection of quantum computing and machine learning. It investigates how the unique capabilities of quantum computing
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This research project aims to establish the theoretical and algorithmic foundations of quantum adversarial machine learning, an emerging field at the intersection of quantum computing and machine learning. It