243 web-programmer-developer-"https:"-"https:"-"https:"-"https:"-"https:"-"https:" positions at University of Nottingham
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Student Recruitment Team. This role provides strategic leadership for the University of Nottingham's international student recruitment activities across allocated regions of responsibility. You will develop
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). This studentship will include a placement at Astra Zeneca, Cambridge and is part of a broader Medical Research Council Programme grant focused to understand mucus regulation in severe asthma. The project will
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Technology, The University of Nottingham. Applicants are invited to undertake a three-year PhD programme in partnership with industry to address key challenges in on-platform manufacturing engineering. The
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Rolls-Royce University Technology Centre (UTC) in manufacturing and On-Wing Technology, The University of Nottingham. Applicants are invited to undertake a three-year PhD programme in partnership
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resolving both simple and complex issues. Support the service to recruit and train Support Workers and maintain a database of their availability and skill set. Identify areas for continuous improvements
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operations, including REF preparation, research governance, ethics, PGR operations and research reporting. Line manage and develop professional services staff, supporting performance, recruitment and workforce
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For You Personal Tutoring Programme. This role is focused on ensuring we deliver the best possible experience for our students. The purpose of the role is to support the Here for You programme, providing a
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to identify areas for research, develop research methods and extend their research portfolio. This work is international in scope and covers a wide range of different substantive issues and contexts. About the
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. About the role You will be responsible for managing the daily activities of a team of recruitment assistants, motivating and developing them to deliver excellent service. You will play a pivotal role in
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focuses on developing cutting-edge statistical/machine learning methods for fitting complex, multi-institutional network models to partially observed hospital infection data. This research will directly