Senior Researcher in Probabilistic Machine Learning for AI Governence

We are seeking

a full-time Senior Researcher to join the Bayesian Governance Lab, led by Professor Maike Osborne, in the Department of Engineering Science (central Oxford), working in close collaboration with the Oxford Martin AI Governance Initiative. The post is fixed-term for two years. The AI systems that most demand assurance learn, act and change by the week, so evaluating them is a problem of sequential Bayesian inference and experimental design rather than of static benchmarking. You will lead a strand of research on Bayesian methods for the evaluation and monitoring of AI systems, publish your findings, lead the lab’s open-source software, translate results into policy-facing outputs, and guide research assistants and students. You should hold a PhD/DPhil in machine learning, statistics or a closely related discipline, with post-qualification research experience and a strong publication record, and have specialist knowledge of Bayesian machine learning or applied probability (for example Gaussian processes, sequential inference or Bayesian optimisation). Familiarity with the evaluation or governance of AI systems is desirable. Whilst the role is a grade 8 £49,119 - £59,955 per annum, we would be willing to consider candidates with potential but less experience or qualification who are seeking a development opportunity, for which an initial appointment would be at grade 7 £39,424 - £47,779 per annum where the individual will undertake all the duties but with increased supervision and/or less responsibility. Where a post is underfilled, a development plan will be put in place stating clear milestones which must be met by the individual in order to be promoted to the substantive grade.