This PhD position at Eindhoven University of Technology focuses on developing innovative, data-driven inspection management and risk assessment methodologies for safety critical systems, with a practical emphasis on vertical transport such as lifts and escalators. The project aims to modernize safety certification frameworks by leveraging AI and IoT technologies, moving beyond traditional visual inspections and reactive approaches to proactive, data-driven risk assessment and optimized inspection planning. The research will utilize operational data from lift controllers and historical event records to enhance diagnostic and predictive capabilities for individual lifts, integrating probabilistic reliability analysis to forecast current and future safety levels.

The candidate will explore novel methodologies for data collection, model transfer across heterogeneous systems, uncertainty modeling, and explainability in AI-driven safety assessments, ultimately contributing to the design of future safety certification standards. The position is embedded within the Operations, Planning, Accounting and Control Group (OPAC) at the Department of Industrial Engineering & Innovation Science, offering a collaborative and interdisciplinary research environment. The candidate will work closely with Liftinstituut, a leading European certification body, and will be expected to publish research findings in international journals and conferences.

Applicants should have a master’s degree in a relevant engineering or mathematics discipline, strong analytical and programming skills (especially in Python), and fluency in English. The position offers a four-year full-time contract with competitive salary and benefits, including pension, parental leave, training programs, and support for international candidates.

The application process requires submission of a cover letter, CV, references, transcripts, and thesis or working papers. The vacancy remains open until filled, with screening as applications are received.