Please note that this job is open only to current Cardiff University staff who are eligible for Redeployment. Internal Redeployment Only - 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 https://www.gov.uk/government/publications/united-kingdom-security-vetting-clearance-levels/national-security-vetting-clearance-levelsdeveloped-vetting-dv The 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 government partners to produce innovative and practical solutions to pressing problems in defence and security. Have experience of AI/machine learning/deep learning and modern computing tools which implement such methodology. We can offer you the chance to work in a vibrant organisation, with great benefits and opportunities for progression. We are a proud Living Wage supporter. This role is eligible to be offered on a blended working basis, meaning that as well as spending time working on campus you may spend some time working from another location, e.g. your home. The University is committed to offering this flexibility, wherever the role and business need allows, supporting work-life balance. Please contact Prof Jon Gillard ( gillardjw@cardiff.ac.uk ) or Prof Maggie Chen ( chenj60@cardiff.ac.uk ) for an informal, confidential discussion about the role. This post is full-time (35 hours per week) fixed-term for 14 months, starting 1st August or soon thereafter. Salary: £41,064 - £46,049 per annum (Grade 6). Closing date: Thursday, 29 January 2026 Cardiff University is committed to supporting and promoting equality and diversity and to creating an inclusive working environment. We believe this can be achieved through attracting, developing, and retaining a diverse range of staff from many different backgrounds who have the ambition to create a University which seeks to fulfil our social, cultural and economic obligation to Cardiff, Wales, and the world. In supporting our employees to achieve a balance between their work and their personal lives, we will also consider proposals for flexible working or job share arrangements. Applications may be submitted in Welsh, and an application submitted in Welsh will not be treated less favourably than an application submitted in English. Cardiff University is a signatory to the San Francisco Declaration on Research Assessment (DORA), which means that in hiring and promotion decisions we will evaluate applicants on the quality of their research, not publication metrics or the identity of the journal in which the research is published. More information is available at: Responsible research assessment - Research - Cardiff University Main Function To conduct research within AiTASHA research project, an EPSRC funded project supporting an interdisciplinary consortium that also includes Warwick, Southampton, Dundee Universities and the Alan Turing Institute. The project aims to improve the speed and confidence of intelligence analysts’ assessments by building new AI tools that can work alongside human analysts. To contribute to the research record of the School through commitment to carrying out research leading to the publishing of high-quality research. To pursue excellence in research and to inspire others to do the same. Main Duties and Responsibilities Research To conduct research within statistics aligned to the aims of the AiTASHA, research project and to contribute to the overall performance of the School and University by the production of measurable outputs including bidding for funding, publishing in national academic journals and conferences, and the recruitment and supervision of research students. To develop research objectives and proposals for own or joint research including research funding proposals To attend and or present at conferences/seminars at a local and national level as required To undertake administrative tasks associated with the research project, including the planning and organisation of the project and the implementation of procedures required to ensure accurate and timely reporting To prepare research ethics and research governance applications as appropriate To review and synthesise existing research literature within the field To participate in School research activities. To build and create networks both internally and externally to the university, to influence decisions, explore future research requirements, and share research ideas for the benefit of research projects Other To engage effectively with industrial, commercial and public sector organisations, professional institutions, other academic institutions etc., regionally and nationally to raise awareness of the School’s profile, to cultivate strategically valuable alliances, and to pursue opportunities for collaboration across a range of activities. These activities are expected to contribute to the School and the enhancement of its regional and national profile. To undergo personal and professional development that is appropriate to and which will enhance performance. To participate in School administration and activities to promote the School and its work to the wider University and the outside world Any other duties not included above, but consistent with the role. The School of Mathematics The School of Mathematics is a research-led School in Cardiff University, one of the UK’s leading universities, with a reputation for internationally excellent research and high quality teaching. In the recent Research Excellence Framework (REF 2021), 96% of research submitted by the School was rated as `internationally excellent’ or `world leading’. The School has five main research groups: Applied and Computational Mathematics; GAPT: Geometry, Algebra, Mathematical Physics and Topology; Mathematical Analysis; Operational Research; and Statistics. The School engages with industry, young people and the wider community to make our innovative research accessible to a wider audience. The School has a long-standing culture of applied research and direct engagement with a wide range of industrial, government and commercial organisations such as the NHS, Hewlett Packard and the Office for National Statistics. For further information visit: http://www.cardiff.ac.uk/mathematics Essential Criteria Qualifications and Education Postgraduate degree at PhD level in statistics, mathematics, a related subject area or relevant industrial experience Knowledge, Skills and Experience An established expertise and proven portfolio of research and/or relevant industrial experience within the research field of statistics. A strong mathematical background accompanied with practical experience developing and applying AI to real world problems or strong theoretical knowledge and academic experience with AI and adjacent topics. Experience developing software in a scientific computing context, ideally using Python/Pytorch/R, including the use of established libraries used in data science and artificial intelligence research. An understanding of the importance of good practices for producing reliable software and reproducible analyses such as version control, issue tracking, automated testing, package management and literate analysis tools. Knowledge of current status of research in specialist field. Proven ability to publish in national/international and/or other research outputs and ability to be successful in competitive research funding. Communication and Team Working Proven ability in effective and persuasive communication. Ability to supervise the work of others to focus team efforts and motivate individuals. Other Proven ability to demonstrate creativity, innovation and team-working within work. Proven ability to work without close supervision. Desirable Criteria Experience in statistical modelling, Bayesian networks, or graph deep learning models. Relevant professional qualification(s). Evidence of collaborations with industry. Proven ability to work without close supervision Proven ability to adapt to the changing requirements of the Higher Education community. Evidence of ability to participate in and develop both internal and external networks and utilise them to enhance the teaching and research activities of the School. Other requirements Eligible for UK security clearance in principle, e.g., by nationality (British Citizen) or 5 years UK residency etc. and a willingness to undergo and eligibility to pass the Security Check (SC) clearance process once in post, if not already held.