547 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" positions at University of Oxford
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provide advice and guidance to research students. You will manage your own research and administrative activities, within guidelines provided by senior colleagues. You will gather and manage ecological data
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information and be self-motivated with ability to work with initiative and flexibility, knowing when to refer matters to others. The ability to work well under pressure, prioritise workload and give attention
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, and other team members, and contribute to the development of information management systems to improve grant administration across the department. It is essential that you must have a degree or
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that form our core research programme. They will be a cornerstone of the centre, collaborating across our three Research Pillars to generate hypotheses and data to underpin subsequent grant applications and
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of managing financial data, ideally in a finance setting, and will be highly numerate with strong attention to detail. Previous experience of using Oracle would be advantageous. What We Offer As an employer, we
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proof-of-principle repetition-rate and staging experimentation. The successful candidate will perform duties that include developing/using particle-in-cell computer codes hosted on local and national high
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to problems, or to progress key tasks. They will have an excellent standard of computer-literacy and will have the ability to handle numerical and financial data with confidence and accuracy. This is a
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space-time modulation metasurfaces. Responsibilities include collecting and analyzing experimental data, publishing results, and presenting findings at conferences. This role may involve superconducting
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out how you meet the selection criteria for the post, using examples of your skills and experience. Click here for information and advice on writing an effective Supporting Statement. As part of your
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5 years. The appointments will be in the area of statistical quantitative finance/financial econometrics, in particular data science and machine learning applied to quantitative finance