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formation of peroxynitrite determined using a phenylboronic acid spin trap and liquid chromatography-mass spectrometry.[4] This project will make extensive use of green chemistry techniques to address key
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academic papers in top AI and finance venues. We welcome applicants with backgrounds in computer science, artificial intelligence, or computational modeling. Skills required of the applicant: Essential
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in Computer Science / Artificial Intelligence or related discipline. Experience of working with sensors. Strong interest in carrying out innovative research in a health context. The successful
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engineering/electronics engineering, or a related field will be advantageous, along with knowledge of the following: *low-power circuits/system design for ASIC, *Verilog based FPGA based system design
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approaches often provide only limited insight into these effects. This project will use advanced computer simulation, informed by post-operative scans and patient movement data, to understand how variations in
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experts, building a powerful, dual-skill profile. Completing this project will establish you as a leading expert in industrial AI and computer vision, highly sought after in the growing Smart Manufacturing
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with a background in computing or data science who wish to connect technical innovation with human-centred system design. The project supports Northern Ireland’s priorities in Software/Cyber and Life
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, biodiversity monitoring, and climate resilience. The work supports strategic priorities in Environmental Sciences, Software/Cyber. PhD researchers will explore how AI-driven Earth observation, computer vision
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there is less in the way of support for changes in research laboratories. The Microbiology Group in the School of Biomedical Sciences is the ideal test-bed to investigate procedures and approaches. It is a
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., Ntoa, S., Salvendy, G. (eds) HCI International 2023 Posters. HCII 2023. Communications in Computer and Information Science, vol 1833. Springer, Cham. https://doi.org/10.1007/978-3-031-35992-7_2 Familoni