620 computer-programmer-"Multiple"-"U"-"Prof"-"Prof"-"O.P"-"U.S" positions in United Kingdom
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Field
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Training Programme. Position will be for 4 years in the first instance. FTE: 1 (35 hours/week) Contract Type: Fixed Term (Currently until 30/09/2028) This fixed-term post is for a Partnerships Officer to
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access to specialised scientific applications, internally developed programmes and software. About You You will be an IT professional with extensive experience in supporting scientific researchers in a
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equipment not available elsewhere. This project is aligned with the “Dialling up Performance for on Demand Manufacturing” Programme Grant, which will place the student within an active and supportive team
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main workstreams of Assessment and Award, Programme Planning and Delivery and Student Communications and Knowledge ensuring accurate and timely record management across multiple systems across the whole
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students. Providing leadership of a programme team to ensure an outstanding student experience and seamless stakeholder interactions. You will collaborate with a wide range of stakeholders such as: Senior
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a team, customer service skills across any industry could well be an advantage. The department uses multiple computer systems to deliver its services therefore experience using multiple systems is
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to become high-growth ventures. This collaborative programme aims to reshape how knowledge exchange, IP Commercialisation, spinout business creation, and investment attraction are delivered across
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University-led flagship initiative that is driving innovation-led growth across Oxfordshire. The postholder will lead the planning and delivery of a strategic programme of high-profile events that elevate the
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building and conference travel. We also offer a comprehensive and inclusive development programme. We are deeply committed to inclusion, diversity, and the wellbeing of our staff and students. Our dedication
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partners. Main Duties Improve, develop, implement, and apply advanced computational tools and workflows to process, analyse, and interpret large-scale LCMS-based metabolomics datasets across multiple species