203 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" research jobs at University of Oxford
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, Reliability and Teamwork Research Unit. Specifically, they will be working to supervise data collection, cleaning and analysis and helping in the writing up and publication of the results. This will involve
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mutations. Working closely with the PI (Professor Peter Visscher), you will develop new research methodologies, conduct analyses on detailed and complex data, write articles for peer-reviewed journals and
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, income-generating teams and data colleagues, you will prepare and review management accounts, support budgeting, forecasting and planning processes, and deliver clear, insightful financial information. You
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to determine whether the Hubble tension arises from observational issues or from limitations in the current cosmological model by combining lensing information and dynamics of the lens to measure H0
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of Paediatrics at the University of Oxford. The goal of our research is to understand the information that shapes the complex physical architecture of the heart wall, and how it can be disrupted to produce
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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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reports and grant proposals. You should possess a PhD or DPhil (or near completion of) in Machine Learning or Maths. Informal enquiries may be addressed to jakob@robots.ox.ac.uk For more information about
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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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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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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