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conditions. Our work combines traditional statistical methods with advanced artificial intelligence algorithms to identify patterns in disease. We also use qualitative methods to understand lived experiences
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drivers, and how do these intersect to create wet and dry extremes? How can improved representation of SM variability at process scales enhance monitoring and prediction, benefitting SM-dependent
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-world conditions to verify system operation against targets and demonstrate the reliability of the technology for use in backup power, grid stabilisation, and renewable energy integration applications
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bioelectronic system that seamlessly integrates therapeutic functions with continuous monitoring capabilities. The system incorporates cutting-edge technologies in bioelectronics, soft robotics, and materials
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conditions. Our work combines traditional statistical methods with advanced artificial intelligence algorithms to identify patterns in disease. We also use qualitative methods to understand lived experiences
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complex health and social care challenges, particularly in the management of long-term conditions. We combine AI and traditional epidemiology with qualitative methods to develop impactful, real-world
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responsible for maintaining high quality research procedures and will work as part of the team and liaise with three recruiting sites in setting up the study, monitoring participant recruitment, data collection
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We are looking for an excellent communicator and researcher in the area of chronic pain, with substantial experience working with people from minority communities and those with health conditions
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disabled people. As a Disability Confident employer with bronze Athena SWAN recognition (University Silver Award status), we demonstrate sustained commitment to creating equitable opportunities across all
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are developing a communication guide delivered by physiotherapists to improve self-management support for older people living with multiple long-term conditions and their carers in the home setting