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PhD in Safe & Efficient Coordination of Mixed Traffic with Automated Vehicles

KU Leuven · Louvain

Junior 🇬🇧 English
Python

Job description

About the role

We are seeking a motivated researcher to join the Mobility and Industrial Management (MIM) group at KU Leuven. The PhD project focuses on developing safe and efficient coordination strategies for automated vehicles operating in mixed traffic with human drivers, cyclists and pedestrians.

Key responsibilities

  • Design and implement traffic modelling and control algorithms for mixed traffic scenarios.
  • Analyse real‑world traffic data and autonomous‑bus pilot data from Leuven.
  • Develop and evaluate data‑driven driving strategies that improve safety and flow.
  • Assess the network‑level impacts of proposed strategies.
  • Collaborate with academic partners, public transport operators and industry stakeholders.

Required profile

  • Master’s degree (minimum distinction) in engineering, computer science, applied mathematics or a related discipline.
  • Strong analytical mindset and interest in quantitative mobility problems.
  • Ability to work independently and as part of an interdisciplinary, international team.
  • Excellent written and spoken English suitable for research and teaching.

Required skills

  • Python programming (or comparable language).

What we offer

  • Fully funded four‑year PhD position.
  • 80 % research focus on traffic modelling, control and automated mobility, 20 % teaching.
  • Access to real‑world pilot projects and extensive industry collaborations.
  • Opportunity to publish and present results at international conferences.

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Published 4 months ago

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KU Leuven

Louvain