198 data-"https:"-"https:"-"https:"-"https:"-"https:" positions at University of London
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, or trans status or history. More information on our structures and initiatives around EDI, including information on staff diversity networks, can be found on our Equality and Diversity Intranet page .
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Right to work: Applications from job seekers who require sponsorship to work in the UK are welcome and will be considered alongside all other applications. For further information visit the UK Visas
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mitigation priorities for the UK. Candidates should also be experienced in conducting quantitative research and applying spatio-temporal epidemiologic methods, ideally to environmental health data. Further
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financial hardship and promoting equality of opportunity. With a strong focus on data-led strategy, you will develop compelling digital and print fundraising appeals, implement stewardship journeys, and drive
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Responsibilities: Process claims efficiently within agreed service levels Review veterinary invoices, clinical notes, and medical histories. Handling and accurately processing client and patient information
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profile, please refer to the job description below. Further Information To be considered for this opportunity, please submit your Covering Letter and CV (by clicking ‘apply for job’ at the bottom
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all people regardless of age, disability, gender, marital status, parental status, race, religion or belief, sexual orientation, or trans status or history. More information on our structures and
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accordance with the Immigration, Asylum and Nationality Act 2006. Casual work (Approximately 100 hours) / Fixed term Applications are invited for the position of Research Assistant to support data cleaning and
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systems providing critical services to students and staff. Investigate and resolve issues involving data processing scripts and database integrations written in PL/SQL. Collaborate with business
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leaders and policy makers in Thailand; delivering training and support to facilitators and healthcare teams involved in the delivery of the intervention; working with data scientists to review the quality