Yongkuk Jeong

Assistant Professor

KTH Royal Institute of Technology
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Sweden

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Yongkuk Jeong is an Assistant Professor at KTH Royal Institute of Technology in Sweden. His research areas include value-oriented digital services in data-driven production logistics, circular manufacturing systems, and AI-enabled vision systems for order picking. He has published recent articles focusing on technological capabilities in smart production logistics and the application of machine learning in urban logistics. His work also encompasses the assessment of smart shipyard maturity and spatial arrangements using deep reinforcement learning.

Positions (2)

Publisher
source

Magnus Wiktorsson

University Name
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KTH Royal Institute of Technology

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.

4 months ago

Publisher
source

Andreas Archenti

University Name
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KTH Royal Institute of Technology

PhD Positions in Production Engineering, Machining, and Production Systems Modelling at KTH

The Department of Production Engineering at KTH Royal Institute of Technology is recruiting four PhD students for research in sustainable, digital, and advanced manufacturing. Two highlighted positions are: (1) Doctoral student in machining with a focus on process and functional surfaces, and (2) Doctoral student in Production Systems Modelling, in collaboration with Nanyang Technological University (NTU), Singapore. The machining position focuses on advanced component manufacturing, high-precision machining, process optimisation, and functional surface characterisation. Research activities include experimental metrology, high-resolution sensor data analysis, process modelling, simulation, and data-driven methods. The student will join the Manufacturing and Metrology Systems unit and the Precision Engineering and Metrology (PEM) group, working closely with industry partners through Centre X. The Production Systems Modelling position advances digital-twin-based frameworks for production and logistics, enabling improved analysis, simulation, and data-driven decision-making in complex industrial environments. The project is part of a strategic partnership with NTU, and the student will spend up to one year at NTU. Research areas include manufacturing systems, digitalization, multimodal data, and AI. The student will join the Production Logistics research group and collaborate with partners in Sweden, South Korea, Singapore, the US, and Taiwan. Applicants must have a relevant master's degree or equivalent, strong English skills, and a background in mechanical, production, or industrial engineering, or computer science. Experience in control systems, metrology, machine tools, modelling, simulation, AI, or digital twins is beneficial. The positions are fully funded, with monthly salary and employee benefits according to KTH’s doctoral student salary agreement. Employment is full-time for up to four years, with opportunities for international research collaboration and a dynamic, interdisciplinary environment. Application requires certified diplomas, transcripts, proof of language proficiency, CV, application letter, and relevant publications. The deadline for applications is 30 April 2026. For more information and to apply, visit the KTH job portal.

4 months ago

Articles (8)

Collaborators (5)

Magnus Wiktorsson

Professor, Head of Department

KTH Royal Institute of Technology

SWEDEN

Lihui Wang

KTH Royal Institute of Technology

SWEDEN

Erik Flores-García

Assistant Professor

Kungliga Tekniska Högskolan

SWEDEN

Hyun Chung

Chungbuk National University

SOUTH KOREA

Michael Lieder

KTH Royal Institute of Technology

SWEDEN
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