225 web-programmer-developer-"https:"-"https:"-"https:"-"https:"-"https:" positions at University of Nottingham in United Kingdom
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, supported by Innovate UK. The core task will be developing, expanding, and automating sophisticated simulation models of complex dairy farm systems using Python. This role focuses on translating real-time
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This Vacancy is open to employees of University of Nottingham only. Working as part of the Brand team, the postholder is responsible for developing, protecting, and enhancing the university's brand
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days (or pro rata) plus standard bank holidays and five university closure days including closure between Christmas and New Year. • We are committed to staff development through the provision
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This Vacancy is open to employees of University of Nottingham only. Working to the Head of Customer Relationship Management (CRM), the postholder will play a key role in supporting the development
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, preparing and posting journals · Prepare and maintain balance sheet reconciliations · Reconcile pay reports to the general ledger and investigate discrepancies, liaising with internal stakeholders as required
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reputation and sustainability of the sports injury clinic, supporting the performance objectives of the University. This position supports the clinical lead in the delivery, development and governance of all
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. · Our reward scheme grants bonuses of numerous values for excellent work · We are committed to staff development through the provision of training, continued support, and career progression opportunities
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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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, contribute to the development of a dynamic culture of KE and enable robust evidence gathering to document and demonstrate research impact. Success in the role will result in our academics being able to make a
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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