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to analyse datasets Experience in statistical or scientific programming (ideally R and/or Python) Experience in analyzing large and/or complex datasets Interest in quantifying uncertainties for computer models
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to artificial intelligence (AI) (e.g. computer science, engineering, Statistics, and mathematics etc.) The post is available for 30 months, starting on 1 September 2025. If you are still awaiting your PhD to be
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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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, 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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, 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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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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science or a related field near completion* Previous experience in analysing neuroimaging (structural magnetic resonance imaging or low field neuroimaging) data across age-groups Advanced (statistical) data
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non-social paradigms for pre specified research hypotheses. Conducting model simulations, fitting, and recovery, as well as statistical inferences on model outputs, for pre specified research hypotheses
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well as statistical inferences on model outputs, for pre specified research hypotheses. Suggesting further appropriate methods and analyses. Writing manuscripts in to disseminate research findings. Present summaries