PhD Candidate in AI-driven Smart Material Characterisation and Modelling Norwegian University of Science and Technology in Norway

NTNU Norwegian University of Science and Technology is offering a PhD Candidate position in AI-driven smart material characterisation and modelling within the Department of Structural Engineering in Trondheim, Norway.

The position is part of the AIMOS project (Artificial Intelligence for Multiscale Offshore Structures), which develops integrated AI methods for the analysis, design, monitoring, and control of floating offshore systems. The project sits at the intersection of artificial intelligence, material science, and offshore engineering, with a clear focus on developing the next generation of intelligent and adaptive offshore structures.

The PhD research will address the experimental characterisation and computational modelling of smart materials for adaptive offshore structures. The work aims to understand and predict mechanical behaviour such as stiffness variation, response time, and long-term durability, while building computationally efficient models that can be used in structural simulations. The successful candidate will combine experimental investigations, physics-informed modelling, and artificial intelligence to develop predictive material models and assess smart-material-based actuation for offshore use.

The position is closely connected to the SIMLab research group and involves collaboration with other PhD candidates in the AIMOS project, including work on fluid-structure interaction and agentic AI. This is a full-time temporary PhD position with a 3-year employment period. The gross salary normally starts at NOK 580,000 per year, depending on qualifications and seniority.

Eligibility requirements include a relevant Master's degree in mechanical engineering, computer science, or an equivalent field. Applicants should have a strong academic record and must meet NTNU's doctoral programme admission requirements. Very good English skills are required, and some international applicants must provide TOEFL, IELTS, CAE, or CPE results meeting the specified minimum scores.

Preferred preparation includes strong knowledge of mechanical or structural engineering, material mechanics, finite-element analysis, computational plasticity, Python programming, machine learning or other AI-driven methods, and experience with experimental work or data analysis. Personal qualities such as independence, collaboration, communication, curiosity, flexibility, and the ability to work under pressure are emphasized.

Applications must be submitted electronically via Jobbnorge.no by 2026-11-20. The application package should include transcripts and diplomas for Bachelor's and Master's degrees, CV, a copy or draft of the Master's thesis, a project outline (maximum 1500 words/4 pages), a short motivation letter, relevant publications or research work, and names and contact information for three referees. Additional documentation is required for degrees obtained abroad.

For questions about the position, contact Associate Professor David Morin at [email protected]. For recruitment process questions, contact HR Consultant June Hovde at [email protected].