PhD Candidate on Antifragile Traffic Control in Urban Road Networks / PhD Candidate on Antifragile Traffic Control in Urban Road Networks

PhD Position on Antifragile Traffic Control in Urban Road Networks

100%, Zurich, fixed-term

We invite applications for a PhD position in the field of AI-driven Traffic Control and Antifragility in Urban Mobility Systems. The successful candidate will join a dynamic team at the Traffic Engineering Group (SVT) of the Institute for Transport Planning and Systems (IVT), ETH Zurich.

The Traffic Engineering Group (SVT) of the Institute for Transport Planning and Systems (IVT) at ETH Zurich aims to develop scalable optimization systems for operational support in large-scale road networks. Modeling and simulation are powerful tools for the development and validation of traffic management and control strategies in urban and freeway environments. Moreover, data-driven methodologies and machine learning offer new opportunities for optimal traffic management strategies but often lack physical intuition, which presents challenges for large-scale deployment and public acceptance.

Project Background

Urban transport systems are increasingly challenged by growing traffic demands, modal shifts, and black swan events (e.g., pandemics, climate shocks). This position is part of the EU-funded AntifragiCity project that aims to build urban mobility systems capable of not only withstanding these disruptions but also adapting and benefiting from them, thereby continuously enhancing their operational efficiency under stress.

By integrating learning-based traffic control methodologies, we aim to realize adaptive, resilient, and self-improving traffic networks. This involves developing real-time AI models, simulation frameworks, and decision-support tools that can effectively respond to stressors and inform long-term urban mobility policy.

Job Description

You will be expected to conduct research in the following areas:

• Design and evaluation of advanced traffic control strategies using learning-based algorithms
• Development of a simulation framework for stressor analysis and traffic equilibrium modeling
• Integration of predictive analytics and multi-agent reinforcement learning (MARL) into traffic control
• Design of scalable, modular methodologies for real-time disruption response and adaptation
• Contribution to system-level evaluation of antifragile attributes in urban road networks

Additional responsibilities include:

• Publishing in top-tier scientific journals and presenting at leading conferences
• Assisting with BSc/MSc supervision and research proposals
• Teaching within the SVT course programme
• Contributing to the operation of the group and the Institute

Profile

The ideal candidate will have a Master’s degree in computer science, artificial intelligence, transportation engineering, or applied mathematics. A strong background in programming and machine learning is essential. You should be a proactive researcher who thrives in interdisciplinary environments.

Desired Skills and Expertise:

• Strong foundations in machine learning, reinforcement learning, or multi-agent systems
• Experience with traffic modeling, control algorithms, or transport simulation tools (e.g., SUMO, Aimsun)
• Solid knowledge of programming
• Familiarity with AI robustness, fairness, and interpretability is a plus
• Interest in the integration of AI with complex, dynamic systems like urban mobility
• Teamwork and communication skills
• Excellent command of English (knowledge of German is a plus)

Workplace

ETH Zurich is known for its commitment to providing excellent working conditions and fostering an exciting working environment filled with cultural diversity. We offer numerous benefits such as public transport season tickets, car-sharing options, a wide range of sports activities through the ASVZ, childcare services, and attractive pension benefits.

We Value Diversity

In alignment with our values, ETH Zurich promotes an inclusive culture that encourages equality of opportunity and values diversity. We nurture a working and learning environment where the rights and dignity of all staff and students are respected. More information can be found on our Equal Opportunities and Diversity website.

Apply Online

Apply online using the form below. Only applications matching the job profile will be considered.

Deadline for applications: 20 June 2025 (23:59 CET)

About ETH Zurich

ETH Zurich is one of the world’s leading universities specializing in science and technology. Renowned for excellent education, cutting-edge research, and the direct transfer of new knowledge into society, we welcome over 30,000 people from more than 120 countries who find our university to be a place promoting independent thinking and inspiring excellence. Located in the heart of Europe, we collaborate globally to develop solutions for the challenges of today and tomorrow.