Bryan T. Adey

ETH Zurich’s Chair of Infrastructure Management is advertising a PhD position in AI-supported resilience assessment of climate-neutral transport infrastructure . The doctoral project is embedded in the EU Horizon SHIFTIN consortium and focuses on developing stress-testing and surrogate-modelling methods for assessing the resilience of interdependent transport infrastructure systems under climate-related and multi-hazard scenarios. The research connects civil engineering , computer science , environmental science , statistics , and mathematics , with practical applications in design, retrofit, maintenance, and recovery planning at asset, corridor, and network scales. The project context includes roads, railways, and ports, and aims to support climate-neutral, resilient, and biodiversity-friendly infrastructure by 2050. The wider SHIFTIN programme combines circular low-carbon materials, nature-based solutions, monitoring technologies, digital decision-support tools, and a digital twin platform. The PhD student will contribute to AI-supported analytics, network-based and agent-based simulation, uncertainty analysis, explainability, and integration with monitoring and digital-twin data. Eligibility: applicants should hold a Master’s degree in civil engineering, transport engineering, infrastructure systems, environmental engineering, computational engineering, data science, or a closely related field. Strong quantitative and programming skills are expected, preferably in Python. Experience with machine learning, statistical modelling, simulation, optimisation, data analysis, or geospatial/network analysis is desirable. Excellent English is required; German or another European language is an advantage but not mandatory. Funding and terms: this is a full-time PhD position at ETH Zurich within a funded EU Horizon project. The post is fixed-term; no stipend amount is stated in the announcement. Application: apply online via ETH Zurich’s portal by 31 July 2026 . Required documents include a motivation letter, CV, transcripts, degree certificates, and optionally a Master’s thesis or writing sample. Applications by email or post are not accepted. Questions about the position should be sent to Nathalie Dietrich at [email protected] .