Jiayan Zhao

Wageningen University & Research is recruiting a fully funded PhD candidate for a project at the intersection of immersive virtual reality , spatial cognition , and geo-information science . The project, embedded in the Laboratory for Geo-information Science and Remote Sensing (GRS) and the WU-GIScience&RS environment, investigates how people learn, update, and use spatial knowledge in state-dependent environments —situations where the meaning or outcome of a spatial relation depends on hidden or changing conditions. The research focuses on how people understand, navigate, and communicate complex spatial environments, and how immersive VR, movement data, interaction logs, and eye-tracking can be used to study these processes. Research themes include spatial learning , navigation , environmental perception and behavior , predictive and adaptive spatial reasoning, and knowledge transfer across virtual-virtual and virtual-real contexts. The successful candidate will develop VR-based experimental tasks, analyze behavioral patterns, and explore when state-dependent spatial representations generalize beyond the learned environment. Supervision is by Jiayan Zhao (Assistant Professor), with co-supervision by Sytze de Bruin and Arnold Bregt at Wageningen University & Research. The post is suitable for candidates with an MSc or equivalent in cognitive science , environmental psychology , human-computer interaction , geo-information science , or a related field, plus experience in experimental research and immersive virtual environments such as Unity. Strong quantitative analysis skills in R and/or Python and excellent English (C1) are expected. Funding includes a fully funded PhD position with a tailored course program. The salary is listed as €3,059 per month in year 1, rising to €3,881 per month in year 4, on a full-time 38-hour contract. The appointment is initially for 18 months and may be extended for the project duration if performance is good. Application deadline: 2026-08-07. Apply via the vacancy page on the WUR website using the apply button. Submit a CV (max 2 pages) and motivation letter (max 1 page), with a total maximum of 3 pages. Applications must be submitted through the website only.