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learning (FL), where multiple UAVs collaboratively train artificial intelligence models without sharing raw mission data. This supports privacy and efficiency, but it also creates a serious security risk: a
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, Materials Science, or a related discipline. The successful applicant will demonstrate strong interest and self-motivation in the subject and the ability to think analytically and creatively. Good computer
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looking for curious, enthusiastic and hard-working candidates with the following expertise: -- an understanding of concepts in fluid mechanics, and analytical and numerical methods to solve partial
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information storage. However, most DNA storage systems remain passive: data are written, archived, and read. This PhD project will help pioneer a new generation of dynamic DNA data storage systems capable not
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from Rolls-Royce plc. This fully funded PhD project, with support from a leading industrial partner, will explore the development of next-generation intelligent sensing and data analysis techniques
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Quantum Fields, Information, and Next-Generation Cosmological Probes This PhD project will investigate theoretical aspects of quantum field theory in cosmological spacetimes, with a particular focus
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diagnosis methods that combine analytical approaches based on drivetrain physical properties with AI-driven data analysis techniques to enhance the accuracy and effectiveness of fault detection and
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at the Clinical School, University of Cambridge. The GBC provides analytical and data management support to research groups within the Metabolic Research Laboratories (MRL). This covers aspects of genomics such as
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geological field data. You will also design and run high-pressure shear-cell experiments on natural and analogue granular materials at Chengdu University of Technology, develop discrete-element simulations
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Studentship Information Supervisor: Prof Rumiana Ray (University of Nottingham) Secondary Supervisor: Dr Hadrien Peyret (University of Nottingham), Dr Dong-Hyun Kim (University of Nottingham), Prof