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Field
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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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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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microclimates that demand dense sensor networks and reliable data retrieval. This project focuses on developing nature-inspired hardware to deploy Internet of Things (IoT) sensors in forest ecosystems. Combining
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, durability, and environmental sustainability, while addressing cost constraints and net zero objectives. It will include an in-depth review of shortcomings in current design, based on literature review and
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quality monitoring system. Potential applications will initially focus on drinking water distribution networks. The main sources of water pollution are relatively well documented in the literature
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Research Project Nucleic acids are potent triggers of immune responses. The presence of virus-derived RNA or DNA molecules activates nucleic acid sensors inside the host cell, which stimulates protective
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-binding domain and leucine-rich repeat (NLR) genes play important roles as the sensors/receptors of non-self molecules and in activation of immune responses such as transcriptional reprogramming and cell
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wireless sensor networks as well as research and education within Life Science, smart electronic sensors and medical systems. The Department of Electrical Engineering is an international workplace with
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electric machines•Nanomaterials for next-generation electronic and photonic nanodevices•Oxide materials for MEMS piezoelectric and multiferroic sensors/actuators•Solid-state devices such as solar cells