257 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "Univ" "UNIV" positions at University of London in United Kingdom
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and thus a failure to provide this information will mean that the application will not be considered. An answer to any of the criteria such as "Please see attached CV" will not be considered acceptable
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failure to provide this information will mean that the application will not be considered. An answer to any of the criteria such as "Please see attached CV" will not be considered acceptable. Please note
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of the selection 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
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attention to detail and the ability to use data and market insights effectively to support decisions. The post holder will be expected to act with integrity, provide robust commercial, process-compliance and
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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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status, parental status, race, religion or belief, sexual orientation, or trans status or history. More information on our structures and initiatives around EDI, including information on staff diversity
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. 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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. These languages notably power WhatsApp's servers, Uber's software infrastructure, and the NHS information backbone. Two key advantages of message-passing concurrency are that it is higher-level and avoids data-race
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) which is responsible for recruiting patients into all hosted trials, regardless of phase, at Barts Health, coordinating trials from a site perspective and collecting data. The post will cover both the CTU
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. The study integrates clinical, microbiological, and data science approaches to generate evidence and tools for safer, more targeted infection management in hospitalised newborns. Key output involves leading