Senior Researcher in Probabilistic Machine Learning for AI Governence

Chilling Competition; Oxford; Hybrid; GBP 49.000 - 60.000; Vollzeit

Zusammenfassung

Chilling Competition’s Bayesian Governance Lab in central Oxford seeks a Senior Researcher to advance Bayesian methods for evaluating AI systems. You will publish work, steer open-source software, and translate research into policy-relevant outputs while mentoring researchers.

The role requires a PhD with strong publication record and experience in Bayesian ML or applied probability. A two-year fixed-term contract is offered with potential development paths within the department.

Qualifikationen

• PhD/DPhil in ML, statistics or closely related discipline; post-qualification research experience and strong publication record.
• Specialist knowledge of Bayesian machine learning or applied probability (e.g., Gaussian processes, sequential inference or Bayesian optimisation).
• Familiarity with evaluation or governance of AI systems is desirable.

Aufgaben

• Lead a strand of research on Bayesian methods for evaluation and monitoring of AI systems.
• Publish findings and lead lab's open-source software.
• Translate results into policy-facing outputs and guide research assistants and students.

Kenntnisse

Bayesian ML

Applied probability

Gaussian processes

Sequential inference

Bayesian optimisation

Ausbildung

PhD/DPhil in machine learning, statistics or closely related discipline

Jobbeschreibung

central Oxford

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.

Informal enquiries may be addressed to Professor Maike Osborne ([e-mail]).

The Department holds an Athena Swan Bronze award in recognition of its commitment to gender equality.

Keywords: Bayesian inference; Gaussian processes; machine learning; AI governance; AI evaluation

£49,119 to £59,955 per annum: Grade 8