301 web-programmer-developer-"https:"-"https:"-"https:"-"UCL"-"UCL" positions at University of Nottingham
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, numerical modelling, data analysis, and interpretation of results. Alongside this, around 30% of the role will involve contributing to publications and actively supporting the development of future research
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development and recognises the importance of providing structured opportunities, guidance, and encouragement to support your growth each year. This is a part-time, fixed term position available until 30/09/2026
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fixed-term period. This key role will help deliver our comprehensive privacy enhancement programme as we modernise our privacy management framework in response to evolving legislative requirements
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projects from research costing development and efficient submission of quality research applications through to successful awards and the set-up of new research awards. The role holder will provide expert
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skeletal muscle metabolism and how exercise affects it. The post holder will be responsible for the day-to-day running of this programme of work as part of Prof Tsintzas’ research team in the Division
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research strategy. You will work flexibly as part of a team to support the operational delivery and of the School’s world-leading research. You will: develop, deliver, manage and coordinate support and
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offers an exciting opportunity to collaborate with NTEC’s internationally recognised academic team on various projects focused on the development, design, and modeling of future paving materials
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students and other facility users to carry out imaging experiments in a safe and efficient manner, following established procedures and health and safety guidelines. Appropriate continued development and
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international and domestic markets. You will shape market positioning, lead budgets, and drive a high‑performance culture across student recruitment and admissions. In this role, you will: Lead the development
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placement within Siemens Digital Industry Software. Project Overview The project focuses on developing and integrating ML techniques to enhance wall treatments for under-resolved boundary layers in