Doctoral Student in Production Systems Modelling

KTH Royal Institute of Technology invites applications for a fully funded PhD position in Production Engineering, focusing on the modelling of production systems for trustworthy, adaptive, and human-centric manufacturing. The research aims to advance digital-twin-based frameworks for production and logistics, enabling improved analysis, simulation, and data-driven decision-making in complex industrial environments. The project sits at the intersection of manufacturing systems, digitalization, multimodal data, and artificial intelligence, offering a unique opportunity to contribute to the future of sustainable and digitalized industry. The doctoral student will join the Production Logistics research group at KTH and collaborate closely with leading industrial and international partners. The project is co-funded by KTH through its international doctoral collaboration strategy and forms part of a strategic partnership with Nanyang Technological University (NTU) in Singapore. The student will spend a total of one year at NTU, which may be divided into shorter stays, gaining valuable global research experience with partners in Sweden, South Korea, Singapore, the United States, and Taiwan. Supervision will be provided by Professor Magnus Wiktorsson (main supervisor), Assistant Professor Yongkuk Jeong (co-supervisor), and Associate Professor Seung Ki Moon from NTU (co-supervisor). The position offers a strong international research environment, attractive employee benefits, and a monthly salary according to KTH's doctoral student salary agreement. Applicants must hold a second cycle degree (e.g., a master's degree) or have completed at least 240 higher education credits, with at least 60 at the second-cycle level, or possess equivalent knowledge. A M.Sc. in Production Engineering, Mechanical Engineering, Industrial Engineering, Computer Science, or a related discipline is expected. English proficiency equivalent to English B/6 is mandatory. Candidates should demonstrate skills in modelling and simulation (preferably multi-method), knowledge in AI and digital twins, scientific writing, and the ability to work independently and collaboratively. Personal skills such as goal orientation, perseverance, and professionalism are emphasized. Applications must include certified copies of diplomas, transcripts, proof of language proficiency, CV, application letter, and representative publications. All documents should be submitted in English or Swedish, with translations if necessary. The application deadline is 30 April 2026. For further details and to apply, visit the official application link.