17 computer-programmer-"https:"-"FEMTO-ST" "https:" "https:" "https:" "https:" "I.E" research jobs at University of Sheffield in United Kingdom
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. The successful candidate will take forward their own programme of transformative research in the engineering and applications of novel biomedical sensing technologies that are underpinned by state-of-the art
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an interdisciplinary supervisory team and an established Advisory Programme. The student will join the well-funded and friendly Whitfield lab (see blog). Please apply for this project using this link: https
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Investigators. Participate in mandatory study days. Identify self-training needs to the project site lead. Participate in training courses as required by project site lead. Pursue a suitable programme of academic
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in low resource settings. The project, led by Professor Parveen Ali at the University of Sheffield, aims to develop and evaluate an integrated psychosocial care plan to support breast cancer survivors
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programme. This post will be predominantly patient focused, playing a key role in helping to deliver cutting edge gene therapy and experimental medicine trials. The ability to implement good clinical practice
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programme. This post will be predominantly patient focused, playing a key role in helping to deliver cutting edge gene therapy and experimental medicine trials. The ability to implement good clinical practice
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the ability to prioritise and plan own workload to meet agreed protocols and deadlines. Essential Application & interview Clear written and verbal communication skills appropriate for technical reporting and
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in the literature. Plan and prepare several months in advance for publications and conference presentations. Write supporting documents to contribute to and support the work of the Research Group, e.g
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the application statement when you apply. Criteria Essential or desirable Stage(s) assessed at Degree in Engineering, Computer Science, Physics, or equivalent experience in a technical data/control systems role
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and responsibilities Conduct a comprehensive review and synthesis of existing air quality, health and economic data, applying quantitative and computational techniques where appropriate to ensure robust