Pierluigi D'Acunto

Technical University of Munich (TUM) is inviting applications for a 75% Doctoral Researcher position in AI-Driven Conceptual Structural Design for Steel Reuse . The project sits at the intersection of civil engineering , architecture , computer science , materials science , and environmental science , with a strong focus on computational structural design , structural optimization , machine learning , and the adaptive reuse of reclaimed steel elements . The research aims to develop an AI-driven conceptual design platform that can automatically generate efficient, code-compliant structural schemes from inventories of reclaimed steel. This supports circular construction by shifting design from material sourcing for a predefined structure to design based on available reused elements. The project is promoted by the Institute for Advanced Study at TUM and funded by the TÜV Süd Foundation. The doctoral position is led by Prof. Dr. Vittoria Laghi and Prof. Dr. Pierluigi D'Acunto . The work will be based primarily at the Professorship of Structural Design at TUM, with one or more research stays at the Additive Manufacturing and Automation in Construction (AMAC) research group at the University of Bologna. Funding details: the position is funded for three years , part-time at 75% , with remuneration according to TV-L E13 . The start date is expected to be January 15, 2027 . Eligibility highlights include a Master of Science (or equivalent doctoral degree) in Structural Engineering, Architectural Engineering, or a closely related field; strong Python programming skills; and a demonstrated interest in computational structural design. Experience in steel engineering, geometry processing, additive manufacturing, and machine learning is highly desirable. Excellent English is required; German is helpful but not mandatory. To apply, send your application by email to [email protected] by 20 October 2026 . Include a cover letter (max. 2 pages), CV (max. 5 pages), and a list of relevant publications (max. 5 pages) as PDF files, with total size under 10 MB. Applications sent to any other address will not be considered.