Eindhoven University of Technology (TU/e) is offering a fully funded PhD position in Multi-Faceted Visual Process Analytics within the Department of Mathematics and Computer Science. The research focuses on developing advanced Visual Analytics techniques for event sequence exploration and analysis, bridging the fields of Process Mining and Visualization. The project aims to create a unified framework that leverages dynamic, interactive visual tools to make complex process data accessible and actionable, moving beyond traditional static representations. The successful candidate will work within the award-winning Visualization cluster at TU/e, supervised by Stef van den Elzen and Fernando Paulovich, both recognized experts in the field. The cluster has a strong track record in high-dimensional data visualization and has contributed to major conferences and industry applications. Applicants should hold a Master's degree in Computer Science, Mathematics, or Electrical Engineering, and possess strong programming skills in languages such as Qt/C++, Java, or Python. Experience in Process Mining or Event Visualization is advantageous but not mandatory. The position offers a competitive salary (€3,059–€3,881 per month), a comprehensive benefits package including bonuses, pension, paid leave, and tax advantages for internationals, as well as access to excellent training and research infrastructure. The PhD contract is for four years, with a teaching component and opportunities for professional development. Applications must be submitted online via the TU/e portal, including a cover letter, CV with publications, and contact details for three references. The deadline is December 3, 2025, but applications are reviewed on a rolling basis until the position is filled. For more information, candidates can contact the supervisor or HR services. TU/e is an internationally top-ranking university known for its collaborative and innovative research environment.

This PhD position at Eindhoven University of Technology (TU/e) focuses on developing advanced Visual Analytics techniques for event sequence exploration and analysis, with the goal of enabling Multi-Faceted Visual Process Analytics. The project is situated within the Department of Mathematics and Computer Science, the largest department at TU/e, and is part of the renowned Visualization cluster, which has a strong track record in high-dimensional data visualization and visual analytics. The research aims to bridge the gap between process mining—a computational approach to discovering, analyzing, and optimizing business processes from event logs—and visual analytics, which emphasizes intuitive, interactive exploration of complex, multi-dimensional data. Traditional process mining techniques often focus on control-flow and neglect other important process dimensions such as timing, spatial distribution, and resource relationships. This project seeks to overcome these limitations by integrating dynamic, interactive visual tools that make complex process data accessible and interpretable to a broader audience. The successful candidate will work on creating a unified framework that harmonizes process mining and visual analytics, unlocking deeper insights into processes by incorporating temporal, spatial, and relational aspects into visualizations. The project is supervised by dr.ir. Stef van den Elzen (Assistant Professor) and dr. Fernando Paulovich, both of whom are active in the Visualization cluster at TU/e. The cluster is internationally recognized, with award-winning contributions at major conferences and successful industry collaborations. Applicants should have a strong background in Visualization or Visual Analytics, preferably with a master’s degree in Computer Science, (Applied) Mathematics, or Electrical Engineering. Experience in process mining or event visualization is a plus, as are strong programming skills in object-oriented GUI languages such as Qt/C++, Java, or Python. Good communication skills, creativity, analytical thinking, and proficiency in English are required. The position offers a full-time, four-year contract with a competitive salary (scale P: €3,059–€3,881 per month), year-end and vacation bonuses, pension scheme, paid leave, and additional allowances for commuting, home working, and internet costs. International candidates benefit from a tax compensation scheme and support from the university’s Staff Immigration Team. The application process is online only; candidates must submit a cover letter, CV with publications, and contact details for three references. The vacancy remains open until filled, with a formal deadline of December 3, 2025. TU/e provides a dynamic, interdisciplinary, and international research environment, with excellent infrastructure and support for professional development.

This PhD project at Eindhoven University of Technology focuses on developing advanced Visual Analytics techniques for the exploration and analysis of event sequences, with the goal of enabling Multi-Faceted Visual Process Analytics. The research aims to bridge the gap between process mining—a field within business process management that extracts insights from event logs—and visual analytics, which specializes in the interpretation of complex, multi-dimensional data through interactive visualization. Traditional process mining techniques often emphasize control-flow analysis, neglecting other important process dimensions such as timing, spatial distribution, and resource relationships. This project seeks to overcome these limitations by integrating dynamic, interactive visual tools that make complex process data accessible and interpretable to a broader audience. The research will explore the synergy between process mining and visual analytics, developing new frameworks and techniques that incorporate temporal, spatial, and relational aspects of processes. The project is embedded within the Visualization cluster at TU/e, a group with a strong international reputation for high-impact research in visualization and visual analytics, and a history of award-winning contributions and successful technology transfer. Supervision is provided by Dr.ir. Stef van den Elzen and Dr. Fernando Paulovich, both recognized experts in the field. The successful candidate will have the opportunity to contribute to cutting-edge research, collaborate with leading academics, and develop tools that can transform the way complex processes are analyzed and visualized across domains such as business, healthcare, and supply chain management. The application process is managed via Academic Transfer, and interested candidates should follow the provided link for further details and to submit their application.