Research Associate in Statistics University

Position: Research Associate in Statistics University  18 February 2026
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Research Associate in Statistics We are looking for a Research Associate in Statistics to join the Statistics and Data Science team in the School of Mathematics, Cardiff University.

Cardiff University has recently been awarded a significant EPSRC research grant to develop AI methods that can support and enhance intelligence analysis for national security and defence.

The work will be delivered by an interdisciplinary consortium that also includes Warwick, Southampton, and Dundee Universities, as well as the Alan Turing Institute. We will be working closely with UK government defence and national security partners.

The project, entitled “AI Intelligence Triage & Acquisition Support for Human-centred Analysis” (AiTASHA), aims to improve the speed and confidence of intelligence analysts’ assessments by building new AI tools that can work alongside human analysts. Intelligence analysts are routinely required to make high-consequence, defensible assessments from vast, complex and uncertain datasets, for example to identify tell-tale signs that a terrorist cell is preparing an imminent attack.

Analysts must make these assessments rapidly in a highly-pressured and resource-constrained environment, where they face difficult choices of what data to analyse first, and whether to gather additional intelligence, potentially at the cost of delay or increased risk.

Addressing this challenge is becoming increasingly urgent as both the scale and complexity of intelligence datasets, as well as the threat posed to UK safety, are growing, and existing AI support tools primarily focus on the identification and visualisation of patterns within datasets, without due consideration of human understanding or context, defensibility, and representation of uncertainty.

The goal of this ambitious project is to make fundamental advances that will together underpin and enable a future explainable, defensible AI system that can complement, rather than replace, the work of intelligence analysts; recommending which existing data should be prioritised for human review and which potential new data should be prioritised for acquisition.

To address this challenge we will advance the state-of-the-art across multiple component disciplines; in explainable multi-modal deep learning models, in causal statistical models and in human-machine teaming and AI ethics.

The successful candidate will need to be eligible for UK security clearance in principle, e.g., by nationality (British Citizen) or 5+ years UK residency etc. Eligibility criteria and further information on the process can be found on the UK Government security vetting website, see  successful candidate will be asked to provide the following information:
• Your current nationality
• Your nationality at birth
• Other nationality (include dual nationality if applicable)
• Confirmation that you have been residing in the UK for the past 5 years (if you haven’t, please provide details of when and where you resided and the reason)
In this role, you will:
• Conduct research in statistics, with applications to intelligence analysis. This role will involve investigating and developing methods that will allow AI-based models to identify subsets of data with the highest potential for reducing uncertainty of model outputs, leveraging and building on existing methods in ML explainability, interpretability, and uncertainty quantification. The research will focus predominantly on vision, language and multimodal models, and on integration of these models with cutting-edge graph-based statistical methods that have been previously developed by members of the project team to support national security use.
• Work with an exciting interdisciplinary team of academics and external stakeholders.
• Participate in activities to promote the AiTASHA project and its work to the wider University and the outside world

We’d like to hear from you if you:
• Have an expertise and proven portfolio of research in statistics with a strong mathematical background.
• Can work with a tight-knit team of researchers and external…