Research Fellow in Large Scale Choice Modelling

University of Leeds; Leeds; On-site; GBP 41,000 - 49,000; Full time

Job summary

The University of Leeds invites applications for a Research Fellow in Large Scale Choice Modelling to advance state-of-the-art discrete choice methods and apply them to transport, health and environmental data.

Working with Professor Stephane Hess in the Choice Modelling Centre, you will develop computational approaches for large datasets, contribute to open-source software, publish in leading journals and help shape future methodological research.

Qualifications

• Strong background in advanced statistical modelling, econometrics or machine learning.
• Experience with very large behavioural datasets.
• Ability to develop new estimation approaches and contribute to open-source software.

Responsibilities

• Develop computational and methodological approaches for advanced behavioural modelling using large-scale datasets.
• Contribute to open-source software and publish in leading international journals.
• Collaborate with colleagues across transport, health and environmental applications.

Skills

Advanced statistical modelling

Econometrics

Machine learning

Large-scale data handling

Tools

Open-source software development

Job description

Research Fellow in Large Scale Choice Modelling

Company:

University of Leeds

Salary:

£41,064 to £48,822 a year, pro rata

Hours:

Full-time

Location:

Leeds, LS2 9JT

Working pattern:

On-site

Job type:

Temporary

Posting date:

17 Sept 2026

Closing date:

8 Oct 2026

Summary

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.