We are excited to offer a fully funded PhD position at the intersection of machine learning and transportation. The transport sector, both in the UK and globally, faces critical challenges, including severe congestion—which costs London alone £5 billion in lost productivity annually and accounts for 5% of the UK’s GDP. Additionally, domestic transport remains the UK’s highest carbon-emitting sector, contributing to air pollution linked to 43,000 premature deaths annually.

Machine learning holds great promise for tackling these issues; however, effectively integrating diverse data sources – such as weather conditions, event schedules, and multi-sensor data – remains a significant challenge. This PhD position will focus on developing foundational models to address these limitations, aiming to enhance prediction accuracy and model explainability, ultimately contributing to more efficient, sustainable, and resilient transport systems.

We seek a candidate with a strong quantitative background and a passion for advancing machine learning methodologies in traffic prediction. The successful candidate will have the opportunity to collaborate with leading researchers within the UK and internationally, with additional funding available for travel and conference attendance.