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Field
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capable of leveraging signals from terrestrial base stations, non-terrestrial networks such as LEO satellite, and complementary on-board sensors. Specifically, it will: To design reconfigurable airborne
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This self-funded PhD opportunity explores assured multi-sensor localisation in 6G terrestrial and non-terrestrial networks (TN–NTN), combining GNSS positioning, inertial systems, and vision-based
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sensor designs should achieve high sensitivity to very small pressure change, making them suited to wireless motility sensing. The sensor will be created used microfabrication techniques such as soft
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to develop AI models for image reconstruction from data from our ultra-thin fibre-based spatial frequency domain imaging device (SFDI) and also from our custom-built photoplethysmography (PPG) sensor
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(SFDI) and also from our custom-built photoplethysmography (PPG) sensor. Applicant should have experience in time-series processing with appropriate AI models (recurrent networks, LSTM) and experience in
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One fully funded, full-time PhD position to work with Prof. Mahesh Marina in the Networked Systems Research Group at the School of Informatics, University of Edinburgh. The broad aim
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of quantum sensors for acceleration sensing is a key priority due to its potential to revolutionise inertial navigation, environmental monitoring and geological surveying. Presently, the acceleration sensing
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PhD project: Modelling Resilience of Water Distribution Networks Supervised by Rasa Remenyte-Prescott (Faculty of Engineering) Aim: To develop an modelling approach for assessing water network
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): Network-level design and multi-node cooperation (coordination, topology design, distributed/federated learning, etc.) Wireless resource allocation and scheduling under multi-objective KPIs (rate, latency
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Description GENIUS is a Marie Sklodowska-Curie doctoral network funded by the European Commission under the Horizon Europe. GENIUS pioneers a comprehensive approach to address the biggest global challenge