Bryan T. Adey

The Chair of Infrastructure Management at ETH Zürich, led by Professor Dr. Bryan T. Adey, invites applications for a PhD position focused on vehicle sensor and remote sensing analysis for road safety. This opportunity is embedded within the Institute of Construction and Infrastructure Management, part of the Department of Civil, Environmental, and Geomatic Engineering. The position is a key component of a multidisciplinary EU Horizon project aiming to advance safe active mobility and urban transport systems through innovative, human-centred, evidence-based research. The project integrates actual and perceived safety for pedestrians, cyclists, and micromobility users, moving beyond traditional crash-focused approaches. It leverages multi-source traffic, infrastructure, vehicle, and health data, immersive eXtended Reality (XR) experimentation, and explainable Artificial Intelligence to analyse safety-critical situations that are rare, underreported, or ethically challenging to observe in real traffic. The research will inform harmonised assessment methodologies, predictive models, and validated indicators, supporting robust evaluation and comparison of regulatory, infrastructural, technological, and behavioural interventions across Safe System Approach stakeholders. Special attention is given to interactions between users with differing masses and speeds, including e-bikes, e-cargo bikes, and e-scooters, for both personal mobility and urban logistics. Large-scale pilots in four European cities will validate methods in real traffic, facilitate cross-city learning, and ensure applicability under diverse safety, infrastructure, and cultural conditions. The project is implemented by a consortium bridging engineering, behavioural science, XR, AI, urban planning, and policy, delivering actionable, standardised guidance to accelerate safer, more inclusive active and micromobility systems across Europe. The PhD candidate will advance sensor and remote sensing data fusion for urban transport infrastructure safety analysis. Core tasks include designing and implementing a scalable sensing pipeline capable of processing multi-source vehicle sensor, camera, and remote sensing data streams; automating feature and factor identification using machine learning and computer vision models; generating mapping and diagnostic outputs optimized for spatial mapping, risk diagnosis, and predictive safety modelling; and collaborating with international partners to validate and refine the pipeline using real-world data from pilot cities. Applicants should hold a Master’s degree in urban analytics, artificial intelligence, computer science, transport planning/engineering, geomatics, or a related field. Essential skills include machine learning, computer vision, statistics, signal processing, proficiency in programming environments (R, Python), and spatial analysis tools (GIS). Professional proficiency in English is required; knowledge of German is beneficial. ETH Zürich offers a world-class research environment, promoting diversity, sustainability, and independent thinking. The university is located in Zurich, Switzerland, and is renowned for its excellence in science and technology. Applications must be submitted online via the ETH Zurich application portal by 31 July 2026. Required documents include a letter of interest outlining potential research ideas, a CV (with publications and referees), and grades/diplomas from all university courses taken. Screening begins 1 August 2026 and continues until the position is filled. The preferred start date is 1 November 2026, but other dates are possible. For further information, contact Ms. Nathalie Dietrich at [email protected] (no applications via email).

The Chair of Infrastructure Management at ETH Zürich, led by Professor Dr. Bryan T. Adey, invites applications for a PhD position focused on infrastructure intervention effectiveness analysis for road safety. This opportunity is embedded within the Institute of Construction and Infrastructure Management, part of the Department of Civil, Environmental, and Geomatic Engineering. The position is a key component of a multidisciplinary EU Horizon project aiming to advance safe active mobility through a human-centred, evidence-based approach that integrates both actual and perceived safety for pedestrians, cyclists, and micromobility users. The project moves beyond traditional crash-focused methods by capturing near-misses, dynamic interactions, and embodied safety experiences that influence behaviour and mode choice. It leverages multi-source traffic, infrastructure, vehicle, and health data, combined with immersive eXtended Reality (XR) experimentation and explainable Artificial Intelligence, to analyse safety-critical situations that are rare, underreported, or ethically challenging to observe in real traffic. The use of explainable AI ensures transparency and interpretability, supporting trust and policy relevance. Insights from the project are translated into harmonised assessment methodologies, predictive models, and validated indicators, enabling robust evaluation and comparison of regulatory, infrastructural, technological, and behavioural interventions across Safe System Approach stakeholders. Special attention is given to interactions between users with differing masses and speeds, including e-bikes, e-cargo bikes, and e-scooters, for both personal mobility and urban logistics. Large-scale pilots in four European cities, including Zurich, validate methods in real traffic, support cross-city learning, and ensure applicability under diverse safety, infrastructure, and cultural conditions. The PhD candidate will work closely with academic, industry, and public authority partners across Europe. Core tasks include structuring and modelling potential infrastructure interventions to improve urban safety and comfort, developing robust methodologies and indicators (such as surrogate safety measures) to evaluate intervention effectiveness, and applying/tested frameworks in pilot cities. Regular coordination with local stakeholders, especially Zurich’s Dienstabteilung Verkehr (DAV), and international project partners is expected. Applicants should have a Master’s degree in spatial planning, urban analytics, transport planning, or a related field, with strong skills in statistical methods, empirical study design, programming, and spatial analysis (including GIS tools). Professional proficiency in English and working proficiency in German are required. ETH Zürich offers a world-class research environment, renowned for its excellence in science and technology, diversity, and sustainability. The university promotes equality of opportunity and a climate-neutral future. Applications must be submitted online via the ETH Zurich portal before 31 July 2026. Required documents include a letter of interest (with research ideas), CV (with publications and referees), and grades/diplomas. Screening begins 1 August 2026 and continues until the position is filled. The preferred start date is 1 November 2026, but flexibility is possible. For further information, visit the Institute of Construction & Infrastructure Management website or contact Ms. Nathalie Dietrich at [email protected] (no applications via email).