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We are currently inviting applications for two Postdoctoral Research Associates (PDRAs) to work with Professor Robin Thompson at the Mathematical Institute, University of Oxford. These are two fixed
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, operations research, computer science, mathematical finance, or a related field, the successful candidate will demonstrate the ability to develop independent research ideas and contribute to advancing our
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experimentally investigated. About you You should possess a PhD or DPhil (or be near completion of) in the field of engineering, physics or applied mathematics together with relevant experience in the field
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expected to be bioinformatic in nature. Applicants must have a PhD in a relevant subject, experience of macrosynteny analysis and phylogenetic analysis of gene families, and a thorough knowledge of animal
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Atmospheric Dynamics group in AOPP which looks at the role of dynamical processes globally in weather and climate variability, predictability and change. The role will involve detailed analysis and dynamical
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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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The post holder will develop computational models of learning processes in cortical networks. The research will employ mathematical modelling and computer simulation to identify synaptic plasticity
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programming skills for data analysis. Excellent organisational and communication skills as well as ability to work as part of a team are essential. This is a fixed-term appointment available for 1 year. If you
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-established data resources accessed within a secure Trusted Research Environment for large-scale analysis. This role offers excellent opportunities to engage with a broad network of collaborators including
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Engineering, Mathematics, Statistics, Computer Science or conjugate subject; strong record of publication in the relevant literature; good knowledge of machine learning algorithms and/or statistical methods