667 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "University of Kent" positions at University of Sheffield
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or fingertip, to detect changes in blood flow. These changes create a waveform that contains valuable information about the heart and blood vessels. While some researchers have used PPG to estimate blood
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the project's social media and website, supporting the leadership team's communication with funders, and maintaining all necessary management information and records (e.g., timesheets, project documentation
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development. Interested? Apply Now! For more information, please contact Prof. Rob Dwyer-Joyce at r.dwyer-joyce@sheffield.ac.uk. Ready to take the next step? Visit PhD study | MAC | The University of Sheffield
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Professional staff, you will be expected to demonstrate a commitment to the professional behaviours set out in the Sheffield Professional Framework. Please follow this link for further information: Sheffield
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environment. Desirable Application Further Information Grade Grade 4 Salary £25,249 - £26,707 per annum (pro rata) Work arrangement Part-time (80%) Duration 1 April 2026 - 24 December 2026 Line manager
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of driving continuous improvement, change and operational excellence. For further information, you can view the candidate brochure here: Uni of Sheffield - Head of ElectricalServices
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Ability to organise, plan and progress research activities Essential Application/Interview Willingness to tackle unfamiliar tasks and develop new skills Essential Application/Interview Further Information
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applicable in real time or without availability of case-specific data in terms of machine types. To address such problems, recent works have proposed machine learning techniques and data which can be easily
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for designing everything from longer-lasting batteries to more effective medicines. However, a major roadblock exists: understanding the complex data from these experiments is a slow, manual process that can
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treatment window may already have passed. Project Aim: This project proposes the development of an innovative approach that applies computer vision and machine learning to detect early signs of stroke through