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: 30 June 2025 Details Join a project that will combine physics, machine learning, and ultrasonics to design new sensors for the digital revolution in industry. Ultra-thin membranes are produced in many
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significant advancements with the integration of Artificial Intelligence (AI) and Machine Learning (ML) techniques. This PhD research aims to explore the development and application of Process Induced Neural
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subsystems • High performance tunable and reconfigurable oscillators and frequency synthesisers • Application of AI / Machine Learning to physical layer circuitry, signals and waveforms Researchers can expect
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Modelling, DEM simulations and Machine Learning Approaches. You will have access to the excellent training opportunities at the University of Sheffield. A range of highly desirable skills will be learnt
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capable of predicting boiling and CHF in PWR-relevant conditions. Combining improved physical modelling with the potential of machine learning and data assimilation techniques, you will specifically target
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Machine Learning Methods for Autonomous Robot Navigation, Localisation and Pipe Inspection School of Electrical and Electronic Engineering PhD Research Project Self Funded Prof Lyudmila Mihaylova
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/interview) A degree (Bachelor’s, Master’s, or PhD or equivalent experience) in Software Engineering, Computer Networks, Embedded Systems, AI, Data Engineering, or a related subject (assessed at: application
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Self-folding Origami ”Robots” for Cognitive Smart Materials School of Electrical and Electronic Engineering PhD Research Project Self Funded Dr S Miyashita Application Deadline: Applications
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Adaptive Learning in Brain-Robot Interactions School of Electrical and Electronic Engineering PhD Research Project Self Funded Dr Mahnaz Arvaneh Application Deadline: Applications accepted all year
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intelligent sensing, followed by detection of the important events.In the light of autonomous decision making, the project aims at developing machine learning algorithms for knowledge extraction from data