662 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "Univ" positions at University of Sheffield
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effectively selecting cutting tool parameters, machining strategies, and work-holding methods, supported by process data analytics for optimisation. Mentor project team members in applying best practices
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Application/interview Further Information Grade 7 Salary £38,784 - £47,389 per annum Work arrangement Full-time Duration Fixed-term until 30 September 2026 Line manager Professor Rachel Smith Direct reports N/A
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presentations, undertaking some initial analysis of information and collation of materials for inclusion. Maintain document filing systems (electronic and hard copy) for critical Departmental documents and logs
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theoretical experience in human cell culture growth. Essential Application/interview Experience of designing experiments and accurately collecting data with subsequent robust analysis using appropriate
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reception taking care of enquiries from students, graduates, staff and visitors in person, via email and chat functions and telephone, recording enquiries on various information systems as required. Take care
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Interview Further Information Grade 7 Salary £38,784 - £47,389 per annum.Potential to progress to £51,753 per annum through sustained exceptional contribution. Work arrangement Full-time Duration Fixed-term
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website https://sheffield.ac.uk/smph/research/primary-care For informal enquiries about this job contact Chris Burton (health) or Peter Bath (data science and PPIE) chris.burton@sheffield.ac.uk or p.a.bath
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senior postdoc to characterise the epigenomic landscape at time points when the immediate (innate) immune response has subsided, but the immune memory persists. Integrating these data with resistance
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human missions, which could extract the first Martian ice cores. You will combine GIS-based mapping and terrain analyses using data from Mars orbiters with: Numerical ice flow modelling, for example using
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. The aim of this PhD project is to identify the factors which govern sensitivity to these toxins and use this information to develop better cellular models of intoxication. The student will be trained in