436 programming-"https:"-"FEMTO-ST"-"UCL" "https:" "https:" "https:" "https:" "https:" "https:" "P" positions at University of Oxford
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advice on writing an effective Supporting Statement. To discuss the post in more detail, please contact Jennifer Lawson, the Senior Programme Manager, using the contact details below. Only online
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University of Oxford. This is a unique opportunity for you to provide diverse audiences with high-quality experiences and contribute to creative idea development within the wider programme, supporting
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globally competitive programme of research and teaching. The Kennedy Institute is a biomedical research centre uniquely bringing together discovery science and early-stage clinical research, to develop
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. Working closely with the Senior Communications Manager, you will help plan and deliver a wide range of communications and engagement activity, supporting events, campaigns and stakeholder communications
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liaising with the Divisional Office and Head of Student Administration to manage administration of graduate students for Doctoral Training Programs, Scholarships, Sponsorships or industrially-funded
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development towards optimizing and understanding sonochemical nitrogen fixation to help advance our internationally leading programme of research. This work will also contribute towards building a case for a
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cell-based assays. You will possess strong experimental design and data analysis skills, with the ability to independently plan, execute and troubleshoot complex experiments. You will have highly
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by ATi/Innovate UK and Rolls Royce and is fixed-term to June 2029. You will join a world‑leading programme advancing experimental and numerical methods to predict the impact performance of composite
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programming; running an imaging study; blood-brain barrier evaluation; and/or the application of machine-learning methods to large (ideally imaging) datasets. Informal enquiries may be addressed to Professor
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programming; running an imaging study; blood-brain barrier evaluation; and/or the application of machine-learning methods to large (ideally imaging) datasets. Informal enquiries may be addressed to Professor