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 intends 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. At the same time, data-driven methodologies and machine learning offer new opportunities for optimal traffic management strategies but often they lack physical intuition, which creates obstacles towards large-scale deployment and public acceptability.

Urban transport systems face increasing challenges from growing traffic demand, modal shifts, and black swan events (e.g., pandemics, climate shocks). The position is relevant to the EU-funded AntifragiCity project that aims to build urban mobility systems that not only withstand these disruptions but adapt and benefit from them, continuously enhancing their operational efficiency under stress.

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

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

You ideally 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 are 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
• Team working and communication skills.
• Excellent command of English (German is a plus)

• Your job with impact: Become part of ETH Zurich, which not only supports your professional development, but also actively contributes to positive change in society
• We are actively committed to a sustainable and climate-neutral university
• You can expect numerous benefits, such as public transport season tickets and car sharing, a wide range of sports offered by the ASVZ, childcare and attractive pension benefits

ETH Zurich is a family-friendly employer with excellent working conditions. You can look forward to an exciting working environment, cultural diversity, and attractive offers and benefits.

In line with our values, ETH Zurich encourages an inclusive culture. We promote equality of opportunity, value diversity and nurture a working and learning environment in which the rights and dignity of all our staff and students are respected. Visit our Equal Opportunities and Diversity website to find out how we ensure a fair and open environment that allows everyone to grow and flourish.

We look forward to receiving your online application with the following documents:

• A short (1 page maximum) motivation letter describing how the past experience and motivation fits the profile sketched in this call
• A full CV
• Copies of diploma/academic transcripts
• Contact details of two referees

Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered.

Further information about the SVT group and the IVT can be found on our website. Questions regarding the position should be directed to Dr. Anastasios Kouvelas (email: [email protected]) or Dr. Michail Makridis (email: [email protected]) (no applications).

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

ETH Zurich is one of the world’s leading universities specialising in science and technology. We are renowned for our excellent education, cutting-edge fundamental research and direct transfer of new knowledge into society. Over 30,000 people from more than 120 countries find our university to be a place that promotes independent thinking and an environment that inspires excellence. Located in the heart of Europe, yet forging connections all over the world, we work together to develop solutions for the global challenges of today and tomorrow.