PhD scholarship in Digital Platform-based Micromanufacturing System
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If you are building your career as a scientist in digital manufacturing, industrial AI, and data-centric production systems—and you are looking for a PhD where your research will contribute to the next generation of intelligent micromanufacturing—this opportunity is for you.
At DTU, you will contribute to the development of digital infrastructures that enable manufacturing systems to become connected, autonomous, and data driven. Working at the intersection of manufacturing engineering, artificial intelligence, and software platforms, you will develop technologies that integrate heterogeneous production data, support AI-driven decision-making, and advance intelligent manufacturing. Through close collaboration with leading industrial and academic partners, you will build a unique research profile combining scientific excellence with hands‑on experience in developing scalable digital solutions for advanced manufacturing.
The PhD position is part of the Horizon Europe Marie Skłodowska-Curie Actions (MSCA) Doctoral Network MicroMan4Health – Data-Centric Micromanufacturing Platform Towards Added Value in the Health Sector (https://www.microman4health.eu/).
The doctoral project is hosted within the Section of Engineering Design and Manufacturing Systems at the Department of Civil and Mechanical Engineering, DTU. You will develop an open digital platform for micromanufacturing built around a secure and scalable data lake integrating heterogeneous production data. The platform will enable plug‑and‑play AI microservices for predictive maintenance, process monitoring, and real‑time analytics, validated on open‑architecture metal powder bed fusion systems. By combining manufacturing engineering, industrial AI, and digital platform technologies, the project will contribute to the next generation of intelligent, data‑centric manufacturing systems.
Responsibilities and qualifications
Your overall purpose will be to develop an open, digital platform for data‑centric micromanufacturing that transforms heterogeneous production data into actionable manufacturing intelligence. The project will establish a secure and scalable data lake capable of integrating multimodal data from advanced micromanufacturing processes, enabling AI‑driven services for predictive maintenance, process monitoring, and real‑time decision support. By shifting from machine‑parameter‑driven fabrication to data‑centric process intelligence, your research will contribute to the digital foundations of next‑generation, interoperable micromanufacturing systems for healthcare applications.
Your primary tasks will be to develop a scalable manufacturing data lake for multimodal production data and design an open platform supporting plug‑and‑play AI microservices. You will develop AI methods for predictive maintenance and process monitoring, while integrating heterogeneous manufacturing data from multiple sources and technologies. Furthermore, you will validate the platform on open‑architecture metal powder bed fusion systems and evaluate its scalability, interoperability, and real‑time analytics capabilities. Finally, you will disseminate research findings through scientific publications and collaboration with industrial and academic partners.
We are looking for a motivated candidate with strong knowledge of digital manufacturing, Industry 4.0, cyber‑physical production systems, or smart manufacturing. The ideal candidate has experience with programming and software development, such as Python or similar, as well as knowledge of data engineering, database technologies, or data integration for industrial applications. Knowledge of machine learning, data analytics, or AI methods for manufacturing applications is also required. Experience with manufacturing data acquisition, industrial sensors, or production monitoring will be considered an advantage, together with an understanding of manufacturing processes and quality assurance methodologies. Furthermore, the candidate should be able to work independently, manage research activities, and collaborate effectively in an international and multidisciplinary environment.
Special requirements
- Applicants must comply with the MSCA Mobility Rule. At the time of recruitment, candidates must not have resided or carried out their main activity (work, studies, etc.) in Denmark for more than 12 months during the 36 months immediately preceding recruitment.
- Applicants must be doctoral candidates (i.e., not already hold a doctoral degree) and be eligible under the MSCA Doctoral Network rules at the time of recruitment.
- Short stays such as holidays, compulsory national service, or time spent as part of a refugee procedure are not considered.
You must have a two‑year master's degree (120 ECTS points) in Mechanical Engineering, Manufacturing Engineering, Computer Science, Data Science, Software Engineering, or a similar degr