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of the department or wider University. Administrators may work in any area of the University; with large groupings in HR, Finance, and School/College Hubs. You will be able to develop a wide range of skills, both
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(HPB). The medical oncology grouping sees close to 550 new cases of these cancers a year. There is a large active clinical trials programme that spans phase 1 to phase 3. These patients have a poor
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after 12 months service. Apprentice Grade 6 Full Time / Fixed Term for 19 Months Apprenticeship Standard: Data Analyst – Level 4 Training Provider: QA Closing date: 20 July 2025 - please upload a CV with
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the handling and management of sensitive information/issues. A high degree of initiative, personal judgement, resourcefulness, flexibility, and a self-motivating approach. Ability to work effectively in a large
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the translation of new discoveries into health applications. The Institute is a Strategic Research Centre and supports a large community of academics across campus as well as hosting 650 square foot of laboratory
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associated with large elements of work; leading/project managing a team to devise and implement a new and/or revised process (e.g. new programme or a recruitment drive); making a sustained contribution to
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proficient IT skills, including the wider MS Office suite of programmes including Excel and PowerPoint. Experience of working with databases and analysis of large data sets. Knowledge of Blackbaud CRM is
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. Familiarity with big data technologies principals (e.g., Spark, Hadoop) and BI tools (e.g., Power BI, Tableau). Strong programming skills (e.g. SQL, Python, Java, or similar languages). Ability to exercise a
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for the University of Birmingham Background Over the next decade, our aspiration is to establish Birmingham in the top 50 of the world's leading universities. That's a pretty big aspiration, and high-quality digital
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and refine algorithms and models for large-scale language processing tasks, with a focus on healthcare data Contribute to developing new models, techniques and methods for clinical machine learning