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inference attacks, to mitigate privacy leaks in MMFM. You will hold a PhD/DPhil (or be near completion) in a relevant discipline such as computer science, data science, statistics or mathematics; expertise in
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of Social Sciences but will also work also closely with colleagues in Social Statistics and Computer Science. The work shall be carried out in line with the grant application granted originally by the ERC (as
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techniques from statistical physics, Bayesian inference, and complex systems theory to address challenges posed by noisy and incomplete data. Depending on the results obtained in the first year, the post can
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, and market and protocol design. The postholder should hold a relevant PhD/DPhil or be near completion in one of the following: Economics, Finance, Operations Research, Statistics, Econometrics
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developing characterisations of network models and interactions with methods in statistical machine learning. The post holder provides guidance to junior members of the research group including project
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applicants for a 6-month paternity leave replacement who have a strong interest in using computational methods such as cognitive and psychophysiological modeling, (Bayesian) statistics and optimal experimental
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or study coordination, or at least active involvement in human studies during your doctoral studies Advanced knowledge in statistics and scientific publishing Experience with methods such as BIA
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, and market and protocol design. The postholder should hold a relevant PhD/DPhil or be near completion in one of the following: Economics, Finance, Operations Research, Statistics, Econometrics
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base, the partnership will bring together the University of Oxford’s expertise in statistics, mathematics, engineering and AI with industry scientists. Within the partnership, small research teams will
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design, power calculations, and statistical methods, with scientific rigour in planning and interpreting experiments. Skilled in scientific writing, data presentation, and teamwork; maintains accurate