Radboud University is seeking a motivated PhD candidate to investigate the individual dynamics of fatigue within the Behavioural Science Institute (BSI), Faculty of Social Sciences. This four-year, fully funded position offers the opportunity to contribute to innovative research on how fatigue fluctuates in daily life, using advanced time series analysis and Ecological Momentary Assessment (EMA) data. The project aims to develop a new conceptual model of fatigue dynamics, starting with analysis of existing datasets, followed by studies involving individuals with burnout complaints and a field experiment to alter fatigue patterns in real-world settings. The successful candidate will join the Work, Health and Performance (WHP) group and the Radboud Ecological Momentary Assessment Center (REMAC), collaborating with researchers across psychology, neuroscience, and related fields. Supervision will be provided by Dr Erik Bijleveld, Dr Fred Hasselman, and Prof. Sabine Geurts. The BSI is renowned for its interdisciplinary research, supportive environment, and commitment to open and team science. The WHP group focuses on work behaviour, health, and performance in dynamic organizational contexts, aiming for both theoretical and societal impact. As a PhD candidate, you will co-design, conduct, analyze, and present research, contributing to several publications that will form your thesis. You will also have a 10% teaching load and the opportunity to work towards a University Teaching Qualification (UTQ). The position offers a competitive salary (€3,059–€3,881/month), 8% holiday allowance, 8.3% end-of-year bonus, flexible working conditions, generous annual leave (30 or 41 days), pension plan, and access to training and development schemes. Dual Career Coaching is available for partners seeking employment in the Netherlands. Applicants should hold a Research Master’s degree in Psychology or a related field, possess strong academic and data analysis skills, and be interested in interdisciplinary research on fatigue. Experience with R/RStudio, EMA data, and time-series analysis is preferred but not required. Candidates who do not meet all requirements are still encouraged to apply. The application deadline is 6 January 2026, with interviews scheduled for 19 January and a preferred start date of 1 March 2026. For more information and to apply, visit the official job posting or contact Dr Erik Bijleveld at the provided email address.