We are looking for a highly motivated researcher, whose expertise lies in statistics, to work with Prof Theodore Kypraios on a project at the forefront of infectious disease modelling. The role focuses on developing cutting-edge statistical/machine learning methods for fitting complex, multi-institutional network models to partially observed hospital infection data. This research will directly support nowcasting (for enhanced situational awareness), forecasting (to assess plausible outcomes in a business-as-usual scenario), the evaluation of control measures, and formal cost-effectiveness analyses of potential interventions. This is an exciting opportunity not only to advance novel statistical methodology, but also to apply it directly to the pressing challenges of healthcare-associated infections (HCAIs) and antimicrobial resistance (AMR) which areas recognised as national public health priorities, offering potential for real, measurable impact on public health, clinical decision-making and healthcare policy.

This post is funded by a NIHR Healthcare Protection Research Unit in collaboration with colleagues at the University of Oxford and the UK’s Health Security Agency (UKHSA). You will take part in regular consortium meetings, give presentations and write reports and papers to communicate your findings. You will have the opportunity to develop and apply innovative statistical methods, publish in high-impact journals, and provide expert advice across disciplines. There will also be opportunities to help supervise undergraduate and postgraduate project students.

We believe that talented and inclusive teams deliver the highest quality research and are seeking applications from high quality candidates who enhance the diversity of our existing team. The School is committed to creating opportunities for people traditionally under-represented in Mathematical Sciences and strives to maintain an environment where people can be their authentic selves.

You will be able to carry out duties to the highest standard and to evidence how through your experience you will:

Undertake original research of international excellence.

• Develop research objectives and proposals for own and/or collaborative research area.

• Prepare papers for publication in leading journals and/or contribute to the dissemination at national/international conferences, workshops and meetings resulting in successful research outputs.

• Identify opportunities and assist in writing bids for research grant applications. Prepare proposals and applications to both external and/or internal bodies for funding, contractual or accreditation purposes.

We are looking for a confident, organised researcher who can evidence:

• A PhD, or equivalent in statistics, machine learning, data sciences, or closely related discipline, OR near to completion of a PhD

• Expert knowledge of statistical modelling, statistical inference and use of relevant software (e.g. R/Python) both for data processing, visualisation and programming.

• Excellent communication and organisational skills.

• The ability to work independently and as part of a multidisciplinary and multicultural team.

• Networking, actively engaging with and valuing other areas and diverse groups.

This full-time post is available from 5 January 2026 [or as soon as possible thereafter] and will be offered on a fixed-term contract for a period of 24 months initially, with the possibility of a further extension of another 24 months. Many of our team have flexible working patterns so we’re open to discuss flexible working arrangements with you.

If it sounds like you would be a good fit, we look forward to hearing from you.

For information about the School of Mathematical Sciences and active research themes see: http://www.nottingham.ac.uk/mathematics/index.aspx.

Informal enquiries may be addressed to Prof. Theodore Kypraios email: theodore.kypraios@nottingham.ac.uk. Please note that applications sent directly to this email address will not be accepted.

To find out more about the People and Culture in the School of Mathematical Sciences please visit our website: https://www.nottingham.ac.uk/mathematics/edi/edi.aspx