130 parallel-and-distributed-computing-"Meta"-"Meta" positions at University of Bristol
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to continually up-date personal exercise knowledge. Through a varied work program flexibility is required to deliver across our Class, Health Minds, PT as well as gym floor supervision at one of our Health
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the molecular mechanisms of early events that lead to the degradation of nonsense mRNAs. Showing a high degree of independence, you will drive an ambitious research programme to determine the structure and
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://engineering.blogs.bristol.ac.uk/category/engineering-includes-me/ Contract type: Open ended Work pattern: Full time Grade: K Salary: £49,559 - £55,755 per annum School/Unit: School of Computer Science This advert will close at23
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. Analyse quantitative and qualitative data to generate insights that inform programme design, delivery, and enhancement. Produce clear, accessible written and visual outputs that communicate complex findings
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and their members with excellent administrative services and support, enabling our student group leaders to run an exciting and varied programme of community building events and activities
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of the following points describe you: Computer and keyboard literate with excellent interpersonal skills. Can work under pressure and alone at times. An ability for 'key questioning' as callers are often confused
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/2026 Work pattern: Full time Grade: J Salary: £42,882 - £48,149 per annum School/Unit: School of Computer Science This advert will close at23:59 UK timeon Sunday 13th July. Interviews are anticipated
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. The person appointed to this role will play a central role in the early evaluation of how the Pledge is being implemented. The research is funded by the NIHR Three Schools Prevention Programme and the
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Fridays 16:00 – 19:00 Various ad hoc hours also available. You will be working on a successful Learn to Swim programme, delivering a range of lessons to children and adults. You will plan and deliver
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that is pioneering transformative edge computing solutions including novel semiconductor devices, design and implementation of energy-efficient hardware, embedded machine learning and sensor-integrated