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and in-depth information about their vision. This could lead to a paradigm shift for monitoring vision in patients with MS – enabling earlier and more reliable detection of vision-related manifestations
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computational design, Industry 4.0 integration, digital twins, and data-driven optimization to enhance manufacturing efficiency. Working closely with the NWCAM2 companies, this project aims to reduce waste, embed
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for fuel system applications. While these methods provide a wealth of knowledge and information, they remain impractical for industrial use. Therefore, AI modelling techniques will be harnessed to develop
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training will be provided. We particularly welcome applicants who are excited about integrating ecological understanding with data-driven methods. There is flexibility to tailor the research to your
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are emerging as promising alternatives, offering potential benefits in carbon reduction, durability, and ageing resistance. However, widespread adoption is limited by inconsistent performance data, insufficient
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should hold a Master’s degree in Economics or a related field (e.g., Finance, Psychology, Maths or Data Science), with a foundational understanding of behavioural/experimental methods and/or econometrics
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progression Sector-leading salary and remuneration package (including 39 days off a year and generous pension schemes). Further Information We are hoping that the successful candidate will start their contract
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is 2:1. Degree in psychology, public health, epidemiology or other health-related discipline. Mode of study: Full-time Start date: 1 October 2026 Additional Funding Information This project is fully
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supporting the setup, calibration, and running of laboratory experiments, including the preparation and configuration of sensors, data acquisition systems, and associated hardware and software components
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the ergogenic aid. Further information: Applicants should have at least a 2:1 in a relevant degree (for example but not limited to Sport Science/Medicine/Rehab, Public Health, Medicine), and ideally a relevant