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Field
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approach is a method that is both formally rigorous and practically efficient for the verification/validation of quantum devices. Candidate’s profile Knowledge of quantum computing and an understanding
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small number of crops, undermines the sustainability and resilience of land use. However, we do not have a good understanding of how land could be used for multiple purposes whilst being sustainable and
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to traditional methods of activation. A precise control of this force can be achieved when the chemical entity that is the subject of the mechanical force (a “mechanophore”) is embedded within a polymeric backbone
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You will join the EPSRC-funded project “Behavioural Data-Driven Coalitional Control for Buildings”, pioneering distributed, data-driven control methods enabling groups of buildings to form
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that require treatment while reducing unnecessary detection of slow-growing cancers. You will play a key role in a large mixed methods project as a qualitative researcher conducting focus groups, interviews and
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studies and interactive AI systems. This position will be funded based on an initial 2-year contract + 2 years extension. The key idea is to apply theories, models, and methods from psychology to improve
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trustworthy operation of navigation systems in complex, GNSS-denied scenarios. The ultimate goal is to provide the navigation research community and industry with tools and methods that ensure continuous, high
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paid. We expect the stipend to increase each year. Only Home students are eligible for funding. The start date is October 2026. The project aims to develop and optimize metal oxide aerogel materials
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applications, facilitating the transition of image-based measurement methods from laboratory research to clinical practice. Digital Image Correlation (DIC) is a well-established, non-contact optical technique
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of the Hub. Our approach enhances T2 (Interconnected QC systems) through verification methods for connected networks, supports T1 (Integrated quantum demonstrators) via hardware-agnostic metrics, and enables