316 data-"https:" "https:" "https:" "https:" "https:" "https:" uni jobs at University of Oxford
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administration, preferably Red Hat Enterprise Linux. Experience in database performance optimisation, capacity planning, and backup/recovery using Oracle RMAN and Data Guard. Excellent problem-solving skills, with
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for hybrid working (typically 60% of working hours on-site and 40% remotely) More information about working at the School can be found on our jobs page . Application process Please upload a supporting
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for university staff. Please see the below 'Job Description' for further details on the role, responsibilities, and selection criteria, as well as further information about the university and how to apply
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criteria listed in the job description. Click here for information and advice on writing an effective Supporting Statement. To discuss the post in more detail, please contact James Lee, Quality Assurance and
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• Act as a source of information and advice to other members of the group on scientific protocols and experimental techniques • Collaborate in the preparation of scientific reports and journal
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project management, to co-ordinate multiple aspects of work to meet deadlines Adapt existing and develop new scientific techniques and experimental protocols Record, analyse, and interpret experimental data
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planning, data analysis and reporting to leadership. Prepare manuscripts, present results at internal and external meetings and contribute to the Oxford Organoid Hub training and outreach. Selection criteria
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effectively within a complex organisational setting, supported by strong analytical skills and experience in gathering, interpreting, and synthesising quantitative and qualitative data for reporting and
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on communications best practice, evaluate the effectiveness of communications activity using data and stakeholder feedback, and contribute to continuous improvement across all channels. You will manage and oversee
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Clinical Practice and UKCRC Clinical Trials Unit SOPs. Responsibilities include day-to-day trial operations, data cleaning and query resolution in collaboration with statistical and health economics teams