PhD Position in Solid Mechanics: Development of Data-Driven Methods (AI-Assisted Design of Fiber-Based Products)

KTH Royal Institute of Technology in Stockholm, Sweden, invites applications for a fully funded PhD position in solid mechanics, focusing on the development of data-driven and AI-assisted methods for the design of fiber-based products. This position is part of the Marie Skłodowska-Curie Doctoral Network ENDURE, which brings together 12 doctoral students, 5 universities, 2 research institutes, and 8 industry partners across four countries. The project is funded by the EU's Marie Skłodowska-Curie Actions (MSCA) and offers a unique opportunity to work at the intersection of academia and industry.

The doctoral candidate will be based at KTH and the industrial partner Yangi AB, gaining interdisciplinary expertise in natural fiber material technology, product design, production engineering, and digital manufacturing (Industry 4.0). The research aims to develop an AI-based hybrid tool for diagnosis and prognosis in the dry forming of cellulose fibers, bridging the gap between advanced simulations and industrial product development.

Supervision: The main supervisor is Professor Artem Kulachenko, with additional contact Sören Östlund. The final decision on supervision will be made upon admission.

Funding and Benefits: The position offers a monthly salary according to KTH's doctoral student agreement (starting at 33,000 SEK/month, approx. 2,991 EUR), with additional mobility and possible family allowances under the MSCA program. The employment is full-time and limited to four years, with the possibility of renewal as per Swedish regulations. The position includes opportunities for professional development, international collaboration, and contributing to industrially relevant research questions.

Eligibility and Requirements: Applicants must not have resided or carried out their main activity in Sweden for more than 12 months in the 3 years prior to recruitment. A master's degree or equivalent (at least 240 ECTS credits, with at least 60 at advanced level) is required. English proficiency equivalent to English B/6 is mandatory. Selection criteria include the ability to work independently, collaborate, maintain a professional approach, and analyze complex issues. Merits include knowledge of numerical methods (FEM), programming (Python, Matlab, C++, Fortran), background in material mechanics or computational modeling, experience with machine learning for physical fields/PDE/GNN and HPC/Big Data, and interest in interdisciplinary collaboration and teaching/lab assistance. Personal qualities are highly valued.

Application Process: Applications must be submitted via the KTH recruitment system. Required documents include a CV, cover letter, degree certificates and transcripts, proof of English proficiency, and representative publications or technical reports. All materials must be submitted by 2025-11-30 (midnight CET/CEST).

About KTH: KTH is a leading international technical university, actively contributing to the transition to a sustainable society. The university offers a creative and dynamic work environment with excellent working conditions and benefits, and values equality, diversity, and equal opportunities as core principles.

For further information, contact Professor Artem Kulachenko ([email protected]) or Sören Östlund ([email protected]).

Apply here