552 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "Univ" "UNIV" positions at University of Oxford
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Capital.com, one of the world's leading trading platforms with millions of users, gaining unprecedented access to proprietary data to conduct frontier research. The project encompasses multiple research
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of information for management reporting, and occasionally taking the lead on small projects to implement new processes and procedures. The post is a permanent, full-time position. You must be educated to at least
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. The ability to work effectively both independently and as part of a team, to build effecting working relationship with colleagues and to handle confidential information appropriately are also essential
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and should also clearly describe how you meet each of the selection criteria listed in the job description. Click here for information and advice on writing an effective Supporting Statement. To discuss
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and should also clearly describe how you meet each of the selection criteria listed in the job description. Click here for information and advice on writing an effective Supporting Statement. To discuss
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and timeline. Once operational, you will oversee initial flow characterisation and data analysis, contribute to the implementation of advanced experimental techniques, and support experiments across
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independently in a laboratory. You are also able to interpret scientific data, analyse data and write factual reports. Excellent organisational skills and ability to manage multiple projects simultaneously
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and data-led insight to colleagues, agency partners and senior stakeholders. Key Responsibilities Lead the development and implementation of a multi-channel paid media strategy across platforms
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for real-time human data processing in interactive settings. Technical expertise in areas such as electrophysiological recording, VR paradigm design, closed-loop algorithm development, or clinical
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of reproducing aerodynamic loads in real time for physical experiments. The project combines numerical modelling, data-driven methods, and laboratory experimentation to advance next-generation real-time hybrid