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The research in this doctoral opportunity will develop a failure model that can represent the combined effect of surface and bending failures in gears to perform reliable health prognostics. Lack
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improves the performance of ROMs, making them more applicable to real-time structural health monitoring, vibration analysis, and control design. This research offers real-world impact across several
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engineering, clinical research, and AI-driven health monitoring. This project will explore large-scale maternal datasets—combining clinical cardiovascular assessments with wearable sensor data—to detect early
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Supervisors: Dr Katherine Finlay, Psychology (Lead) Collaboration Partners: Dr Alexandra Oti, Unravel Health Dr Chanais Matthias, Manchester Metropolitan University Project Overview: Hormone-driven
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Role type: Part-time (0.2 FTE); Fixed-term for 6 months Faculty: Faculty of Medicine, Dentistry and Health Sciences Department/School: Centre for Youth Mental Health Salary: Level A - $85,555 to
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-critical systems. The research will focus on developing AI-powered verification tools, health monitoring algorithms, and compliance assurance techniques that ensure system reliability throughout
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UK Health Security Agency and Nottingham University Business School The mission of the United Kingdom Health Security Agency (UKHSA) is to provide health security for England by protecting
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of Europe’s leading academic departments of population health sciences. The post will suit researchers interested in understanding computers energy usage to improve carbon footprint monitoring and reduce the
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Evaluating the use of longitudinal over-the-counter healthcare sales data as a source of syndromic surveillance for community-based infections UK Health Security Agency and Nottingham University
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the evidence–base needed to understand the impact on health, to inform public policy, and to develop potential mitigation strategies. Traditionally, this information has come from ground monitoring networks