231 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "Here We Are" positions at University of London
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institutional visibility through coordinated, data-led content and campaigns. For a full role profile, please refer to the job description below. Further Information To be considered for this opportunity, please
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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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. Further information To be considered for this opportunity, please submit your application and CV (by clicking ‘apply for job’ at the bottom of this page) before the closing date at midnight on 6th March
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criteria. Please provide one or more paragraphs addressing each criterion. The supporting statement is an essential part of the selection process and thus a failure to provide this information will mean that
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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 initiatives around EDI
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of the relevant Universities' computer systems, competent knowledge of Microsoft Office including Excel is essential for the role. In addition, you should be well-organised, and proactive, have an engaging
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variety of customer queries. While full training will be given for all of the relevant Universities' computer systems, competent knowledge of Microsoft Office including Excel is essential for the role. In
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during the span of the project. The post holder will have technical experience of reporting and visualising strategic information and an understanding of the key performance metrics used within the higher
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, religion or belief, sexual orientation, 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
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at LSHTM. The post-holder must have a postgraduate degree in a relevant topic (ideally Medical Statistics or equivalent) and relevant experience in using regression models for data analysis and statistical