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

PhD Position on Antifragile Traffic Control in Urban Road Networks

100%, Zurich, fixed-term

We invite you to explore an exciting PhD position in the realm of AI-driven Traffic Control and Antifragility within 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) at ETH Zurich.

Project Background

Urban transport systems are facing unprecedented challenges from growing traffic demands, modal shifts, and unforeseen events (e.g., pandemics, climate shocks). This position is part of the EU-funded AntifragiCity project, which aims to develop urban mobility systems that not only withstand disruptions but also adapt and thrive, continuously enhancing their operational efficiency under stress.

By integrating learning-based traffic control methodologies, we strive to establish adaptive, resilient, and self-improving traffic networks. This involves the creation of real-time AI models, simulation frameworks, and decision-support tools that effectively respond to stressors and inform long-term urban mobility policies.

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 will 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 program
• Contributing to the operation of the group and the Institute

Profile

The ideal candidate will hold a Master's degree in computer science, artificial intelligence, transportation engineering, or applied mathematics. A strong foundation in programming and machine learning is essential, as is a proactive approach to research 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 integrating AI with complex, dynamic systems like urban mobility
• Strong teamwork and communication skills
• Excellent command of English (knowledge of German is a plus)

Workplace

ETH Zurich is committed to providing a family-friendly environment with excellent working conditions. You can anticipate a stimulating working atmosphere, cultural diversity, and an array of attractive offers and benefits.

We Offer

• Your job will have a meaningful impact: Be part of ETH Zurich, which actively fosters your professional development and contributes to positive societal change
• We are committed to creating a sustainable and climate-neutral university
• Expect numerous benefits, including public transport season tickets, car sharing, a diverse range of sports offered by the ASVZ, childcare, and compelling pension benefits

We Value Diversity

In alignment with our values, ETH Zurich promotes an inclusive culture. We encourage equality of opportunity, respect diversity, and foster a working and learning environment where the dignity and rights of all staff and students are upheld. Visit our Equal Opportunities and Diversity website to discover how we support a fair and open atmosphere for growth and development.

Curious? So Are We.

We look forward to receiving your online application using the form below. Please ensure to include the following documents:

• A short (1 page maximum) motivation letter highlighting how your past experiences and motivations align with the position
• A comprehensive CV
• Copies of diplomas or academic transcripts
• Contact information for two referees

Only applications matching the job profile will be considered.

About ETH Zurich

ETH Zurich is one of the world’s leading universities specializing in science and technology. We are renowned for our excellent education, cutting-edge fundamental research, and direct transfer of new knowledge into society. With over 30,000 individuals from more than 120 countries, our university fosters independent thinking and an inspiring environment for excellence. Located in the heart of Europe, we connect globally to address the challenges of today and tomorrow.