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and kinematic models with machine-learning-based channel state information (CSI) prediction to enable robust, low-latency connectivity across multi-layer NTN systems. This PhD project sits
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start dates also possible) Email: david.duncan@nottingham.ac.uk About the project We are recruiting applicants for a fully funded PhD studentship in the School of Chemistry at the University of Nottingham
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epidemiology and statistical and mathematical modelling For appointment at grade 7: A4 Normally Scottish Credit and Qualification Framework level 12 (PhD) plus track record of emerging independence within a
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ultrasonic sensors for real-time seal gap measurement. Combine experimental research and mathematical modelling to pioneer innovative sealing solutions. What We Offer Full 4-year Funding for UK applicants
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, Aerospace and Civil Engineering at the University of Sheffield, and embark on a transformative PhD project funded by John Crane Ltd, a global leader in engineering technology. What’s the Project About
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Job Purpose The candidate will contribute to the work of the consortium *Policy Modelling for Health (HealthMod”, 2024-2028) and associated projects, *working with Dr. Andreas Hoehn, Prof. Petra
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performance and explore the use of an ultrasonic sensor for real-time monitoring. Experiment with ultrasonic sensors for real-time seal gap measurement. Combine experimental research and mathematical modelling
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This PhD project is at the intersection of electromagnetism, numerical methods, and high-performance parallel computing, with application towards the design and optimisation of integrated circuits
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processes associated with CIN [1], leveraging single-cell DNA sequencing understand CIN heterogeneity [2], and development and implementation of machine learning and AI models to imaging data [3]. The student
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trust in digital communications and readily bypass conventional security controls. This PhD research proposes to design, develop, and validate a novel, explainable, multi-modal detection framework. By