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Field
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This PhD opportunity at Cranfield University explores how next-generation AI models can be embedded within resource-constrained electronic systems to enable intelligent, real-time performance
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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chemistry and life cycle thinking in early decision-making. AI-based methods and hybrid models, which integrate data-driven and mechanistic modelling, hold significant potential to enhance prospective
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need for materials that can endure extreme conditions while maintaining structural integrity. This Ph.D. project will explore the failure mechanisms in refractory metals and advanced ceramic coatings
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aspects of the research project(s), including design, fabrication, characterization, and modeling of metamaterial fibers and textiles. Develop and optimize fabrication processes for fibers and textiles
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PhD position within the project "What's wrong? Ancient corrections in Greek papyri from Egypt" (AnCo
, of the cognitive, historical, cultural, creative, and social aspects of human life. As an academic community, we strive to create an open and welcoming atmosphere, stimulating everyone to get involved and contribute
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on subjective human judgements or assessments by other AI models, offering no formal guarantees of alignment---raising concerns about trust, especially when these technologies are deployed in real-world scenarios
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well as Mobility Modeling and Simulation. Research topics range from conceptual issues of strategic planning to small-scale analyses of specific street spaces. The chair’s methodological focus is on the empirical
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life balance we offer flexible working hours, variable part-time, job-sharing models and participation in mobile work (up to 50%). You will benefit from our family-friendly and collegial atmosphere, our
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’ is therefore to investigate the influence of glucosinolate-based amines on the formation of Maillard-like products in model systems and foods, to isolate and identify the resulting products and to find