PhD Position in Vehicle Sensor and Remote Sensing Analysis for Road Safety

PhD Position in Vehicle Sensor and Remote Sensing Analysis for Road Safety

100%, Zurich, fixed-term

The Chair of Infrastructure Management at ETH Zurich, led by Professor Dr. Bryan T. Adey within the Institute of Construction and Infrastructure Management, is seeking a dedicated PhD student. This position emphasizes the utilization of vehicle sensors, remote sensing, and machine learning to enhance urban road safety analysis as part of an extensive EU project.

Project Background

This new EU Horizon project aims to promote safe active mobility through a human-centred, evidence-based approach that integrates both actual and perceived safety for pedestrians, cyclists, and micromobility users. Moving beyond traditional crash-focused methodologies, it also examines near misses, dynamic interactions, and embodied safety experiences that affect behavior and mode choice.

The project employs a combination of multi-source traffic, infrastructure, vehicle, and health data, alongside immersive eXtended Reality (XR) experimentation and explainable Artificial Intelligence. This combination allows for the analysis of rare, underreported, or ethically challenging safety-critical situations in real traffic. The project translates findings into harmonized assessment methodologies, predictive models, and validated indicators, facilitating robust evaluation and comparison of various regulatory, infrastructural, technological, and behavioral interventions among Safe System Approach stakeholders.

Special attention will be given to interactions between users with differing masses and speeds, including e-bikes, e-cargo bikes, and e-scooters, for personal mobility and urban logistics. Large-scale pilot programs will take place in four European cities to validate methods in real traffic, encourage cross-city learning, and ensure applicability across diverse safety, infrastructure, and cultural conditions. This multidisciplinary consortium spans engineering, behavioral science, XR, AI, urban planning, and policy, delivering actionable, standardized guidance to enhance safer, more inclusive active and micromobility systems across Europe.

Planning safe urban transport systems is inherently complex, requiring significant investment and adaptation to ever-changing user needs. Modern data collection methods—such as high-frequency on-board vehicle sensors and computer vision imagery—provide real-time, high-resolution insights into these complexities. However, the challenge lies in effectively collecting, processing, and operationalizing these vast quantities of data due to heterogeneous structures and intensive computational needs.

Job Description

This doctorate will contribute to advancements in sensor and remote sensing data fusion for urban transport infrastructure safety analysis. The successful candidate will develop innovative tools and methods that integrate big data, computer vision, and machine learning. Core responsibilities will include:

• Develop a Scalable Sensing Pipeline: Design and implement a software architecture capable of processing multi-source vehicle sensor, camera, and remote sensing data streams.
• Automate Feature & Factor Identification: Train machine learning and computer vision models within the pipeline to automatically detect built-environment infrastructure characteristics and factors affecting micromobility safety and comfort.
• Generate Mapping & Diagnostic Outputs: Ensure the software processes diverse inputs and produces high-quality data outputs optimized for spatial mapping, risk diagnosis, and predictive safety modeling.
• Collaborate via Real-World Pilots: Validate and refine the pipeline using real-world data from pilot cities in close cooperation with international consortium partners.

Profile

• A Master's degree in urban analytics, artificial intelligence, computer science, transport planning/engineering, geomatics, or a related field.
• A solid understanding of machine learning, computer vision techniques, statistics, and signal processing.
• High proficiency in programming environments (e.g., R, Python) and spatial analysis tools (GIS).
• Fluency in English (professional proficiency, written and spoken); knowledge of German is a plus.

Workplace

ETH Zurich is among the world's leading universities in science and technology, recognized for our excellent education, cutting-edge research, and direct knowledge transfer to society. Over 30,000 individuals from more than 120 countries consider ETH a nurturing environment that fosters independent thinking and excellence.

We Value Diversity and Sustainability

In line with our commitment to an inclusive culture, ETH Zurich promotes equality of opportunity, values diversity, and maintains a supportive environment for all staff and students. Visit our Equal Opportunities and Diversity website to learn more about our fair and open environment. Sustainability is a core value, and we are actively working towards a climate-neutral future.

Apply Online

If you are interested in this opportunity, please apply online using the form below. Only applications matching the job profile will be considered.

For further information about the Institute of Construction and Infrastructure Management, please visit our website. Questions regarding the position should be directed to Ms. Nathalie Dietrich at dietrich@ibi.baug.ethz.ch.

We look forward to receiving your application, including your resume and a cover letter outlining your research ideas.

The preferred start date is 1 November 2026, though other dates can be accommodated.