511 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "Univ" "Univ" "Univ" PhD scholarships in United Kingdom
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measurement and stopping rules controlling type-I error with finite-sample guarantees. Quantum statistical modeling: use of quantum relative entropy, Fisher information, and variational quantum circuits
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computer simulations by developing fundamentally innovative and advanced protection strategies. To enhance the reliability and safety of low-voltage networks with a high penetration of power-electronic
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that deliver healthier indoor environments, lower carbon emissions, and long-term building performance. By integrating Passive House and EnerPHit principles with real building data, the research will support the
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the Faculty of Engineering, plus those housed in Plant Biosciences at the Sutton Bonnington campus. Data sets will be generated using simulated and experimental data and these will be used to train networks
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for candidates who can demonstrate strong research potential. Suitable backgrounds include, but are not limited to: Human Factors Law (particularly law and technology, medical law, or data governance) Psychology
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for ‘Course Title’ using programme code: 8050F Research Area: Computing Science select ‘PhD Computer Science’ as programme of study You need to provide the following information in ‘Further Questions’ section
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select ‘PhD Computer Science’ as programme of study You need to provide the following information in ‘Further Questions’ section: ‘Personal Statement’ (mandatory) - upload document or write statement
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
intelligence, particularly in computer vision and deep learning, offer an opportunity to automate and enhance damage assessment by learning patterns from multimodal data. This research seeks to bridge the gap
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geophysical and planetary models. IBM faces several such challenges in practice, many of which are currently approached using Foundation-Model (FM) surrogates. However, certain inverse problems arise in data
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reusable plaque–flow atlas. Key objectives include to: Develop automated computer aided design (CAD) and meshing pipelines to generate a library of arterial geometries representing common geometric