Research Fellow in Large Scale Choice Modelling

Do you have expertise in advanced statistical modelling, econometrics or machine learning with a particular focus on analysing large-scale behavioural data? Are you interested in developing new methodological approaches capable of extracting behavioural insight from increasingly complex and high-dimensional datasets? Would you like to help shape the next generation of behavioural modelling methods with applications in transport, health and the environment?

Understanding human decision making increasingly relies on analysing very large datasets collected through digital technologies, administrative systems, sensors and longitudinal studies. While these datasets offer unprecedented opportunities to understand behaviour at scale, they also present significant methodological challenges. Many of the most behaviourally realistic choice models remain computationally expensive to estimate, limiting their application to modern population-scale datasets.

Working with Professor Stephane Hess and colleagues within the Choice Modelling Centre, you will contribute to methodological advances that enable state-of-the-art discrete choice models to be applied to emerging data sources across transport, health and environmental applications. In particular, you will develop new computational and methodological approaches for advanced behavioural modelling using large-scale datasets.

The successful candidate will have the opportunity to develop new estimation approaches, contribute open-source software, publish in leading international journals and help shape future methodological research in behavioural modelling.

What we offer in return:

- 26 days holiday plus approx. 16 Bank Holidays/days that the University is closed by custom (including Christmas) – 42 days a year
- Generous pension scheme options plus life assurance
- Health and Wellbeing: Discounted staff membership options at The Edge, our state-of-the-art Campus gym, with a pool, sauna, climbing wall, cycle circuit, and sports halls
- Personal Development: Access to courses run by our Organisational Development & Professional Learning team
- Access to on-site childcare, shopping discounts and travel schemes

This role will be based on the university campus with scope for it to be undertaken in a hybrid manner. The University is also open to discussing flexible working arrangements.