657 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "Simons Foundation" uni jobs at University of Sheffield in United Kingdom
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with a team of staff, stakeholders and colleagues Essential Application/Interview Effective communication skills, both written and verbal, report writing skills and with experience of manipulating data
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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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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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creative approaches to problem-solving. Essential Application/Interview Further Information Grade Grade 7 Salary £38,784 to £41,064 Work arrangement Full-time Duration March/April 2026 until January 2027
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-quality documentation. Essential Application/ interview Experience of working with confidential and sensitive information with discretion and professionalism. Essential Application/ interview High level of
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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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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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Award at the University of Sheffield. Imagine being able to check that a powerful quantum computer has performed a calculation correctly without having to repeat the computation or learn the private data
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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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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