Research Fellow in Machine Learning Assisted Choice Modelling

University of Leeds; Greater London; Hybrid; GBP 45,000 - 65,000; Full time

Benefits offered by this job

26 days holiday + 16 bank holidays

Health and wellbeing benefits

Personal development courses

On-site childcare and travel discounts

Job summary

University of Leeds is seeking a Research Fellow in Machine Learning Assisted Choice Modelling to advance AI-enabled discrete choice methods on joint projects with transport, health and environmental domains.

The role combines methodological research with software development, rigorous validation and publication. It offers hybrid working options and opportunities for collaborative, cross-disciplinary impact.

Qualifications

• Expertise in discrete choice modelling and econometric methods.
• Experience with machine learning methods and AI tools.
• Ability to develop open-source software and publish research.

Responsibilities

• Lead methodological research in AI-assisted choice modelling.
• Develop open-source software for modelling and validation.
• Publish results in leading journals and conferences.
• Collaborate with researchers across transport, health and environmental applications.

Skills

Discrete choice modelling

Behavioural data science

Machine learning

Tools

Open-source software

Job description

Research Fellow in Machine Learning Assisted Choice Modelling

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

The University of Leeds is one of the top 80 universities in the world. We have a truly global community, with more than 39,000 students from 170 different countries and over 9,000 staff of 100 different nationalities. Established in 1904, we have a strong tradition of academic excellence, reflected in first‑class student education, along with world‑leading research that has a real impact around the globe.

Do you have expertise in discrete choice modelling, behavioural data science or machine learning? Are you interested in developing the next generation of AI tools that accelerate scientific discovery while maintaining behavioural realism and interpretability?

You will join the Choice Modelling Centre to develop AI-assisted methods for specifying, estimating and validating discrete choice models. The project aims to bring together ideas from machine learning, econometric choice modelling and mathematical psychology. You will investigate how large language models, optimisation algorithms and automated model search methods can support researchers in constructing robust behavioural models without replacing scientific judgement. The emphasis is on interpretable AI processes that complements econometric theory and domain expertise.

The successful candidate will lead methodological research, develop open-source software, publish in leading journals, and collaborate with researchers across transport, health and environmental applications.

Visa Eligibility

Please note that this post may be suitable for sponsorship under the Skilled Worker visa route but first‑time applicants might need to qualify for salary concessions. For more information please visit: www.gov.uk/skilled-worker-visa.

• 26 days holiday plus approx.16 Bank Holidays/days that the University is closed by custom (including Christmas) – That’s 42 days a year!
• 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 are also available.

And much more!

Professor Stephane Hess, Professor of Choice Modelling