Patrick Vandewalle

KU Leuven is advertising a PhD scholarship within the RUN2GETHER project for research at the intersection of computer vision , artificial intelligence , biomechanics , and smart infrastructure . The project focuses on runner mapping using cameras and computer vision , then using those data to study running load , motivation , and how collective running behaviour affects bridges , running tracks , and other infrastructure. The work involves sensors , experimental data , signal analysis , and interdisciplinary collaboration across engineering , biomechanics , psychology , and AI . Eligible candidates should have a Master’s degree in Electrical Engineering, Computer Engineering, or a related field . The post is aimed at a motivated researcher interested in combining computational methods with human movement and infrastructure analysis. This is a PhD opening at KU Leuven . No deadline, stipend amount, or detailed funding package is stated in the post. Interested applicants should follow the KU Leuven job link and review the project page for full application instructions.

RUN2GETHER at KU Leuven is an interdisciplinary PhD opportunity focused on mapping runners using AI and computer vision . The project uses running training groups and events as living laboratories to study how human movement, social identity, technology, and urban infrastructure interact. The PhD research in this position centers on video and data analysis in real-life environments , with the goal of extracting useful information such as pose, step frequency, synchrony , and other movement parameters. The recorded data will come primarily from video, supplemented by wearable sensor data such as IMU measurements , enabling AI-based tracking of individual runners. The work combines controlled experiments with measurements taken during real-world running events. An additional part of the project is the development of an interactive interface such as a chatbot or visual tool to efficiently collect subjective data from runners while they are running. The broader RUN2GETHER project also aims to advance understanding of collective running, health, social cohesion, and the interaction between runners and urban infrastructures such as bridges and running tracks. The position is embedded in a larger initiative with three PhD students working closely together across disciplines including engineering, sports psychology, movement and rehabilitation sciences, biomechanics, and structural engineering. The primary work location is KU Leuven Campus De Nayer in Sint-Katelijne-Waver. Eligibility highlights: applicants should have a Master's degree in Electrical Engineering, Computer Science, or a related field; strong interest in digital signal processing, machine learning, and computer vision is expected; experience or interest in biomechanics and experimental data collection is an asset. The posting also emphasizes a multidisciplinary mindset, creativity, initiative, independence, teamwork, communication skills, responsibility, and willingness to take on some teaching tasks. Candidates who have not yet graduated but will have a strong CV by the deadline are encouraged to apply. Funding note: the successful candidate is expected to write a personal funding application with support from the supervisors. Specific stipend or tuition details are not provided in the posting. Application window: deadline is 14 August 2026 at 23:59 Brussels time. Contact: Prof. dr. Patrick Vandewalle ( [email protected] ).

RUN2GETHER is an interdisciplinary KU Leuven PhD project at the intersection of human movement, social identity, technology, and urban infrastructure. The project treats running groups and running events as a living lab and investigates how collective running can contribute to healthier citizens and more sustainable cities. The advertised doctorate focuses on the analysis of video and other real-world data captured during group runs and running events. Using AI-based techniques, the project will extract biomechanical variables such as pose, cadence, and synchrony from video, supported by on-body sensor data including IMU measurements. The research will combine controlled experiments with observations in authentic event settings, and will also involve the development of an interactive interface to efficiently collect subjective data from participants while they are running. This vacancy is hosted by KU Leuven and linked to the EAVISE research group, with the main workplace at KU Leuven Campus De Nayer in Sint-Katelijne-Waver. The broader project brings together several disciplines, including biomechanics, social and sports psychology, civil/structural aspects of running infrastructure, and machine learning. The project aims to understand how shared social identity influences movement synchrony, physical loading, and interaction with infrastructure such as bridges and running facilities, while also contributing to citizen science and infrastructure monitoring. Applicants should have a master's degree in industrial engineering sciences, electronics-ICT, or a related field. Strong interest or experience in digital signal processing, machine learning, and computer vision is expected, and knowledge of biomechanics and experimental data collection is a clear advantage. The position particularly suits candidates with a multidisciplinary mindset who are creative, self-driven, and comfortable working in an international and cross-disciplinary environment. Candidates should also be willing to take on teaching-related tasks and administrative or technical support activities within the research group and faculty. The offer includes research on machine learning-based computer vision methods for measuring running-related parameters, development of a user interface for collecting participant feedback, supervision of master theses, teaching assistance, and support for activities within EAVISE and the Faculty of Industrial Engineering Sciences. Interested candidates can contact Prof. dr. ir. Patrick Vandewalle at [email protected] . Applications must be submitted through the KU Leuven recruitment portal before 2026-08-14 23:59 (CET).