PhD Candidate in Data-Driven Methods and Sustainable Materials for Offshore Wind University of South-Eastern Norway in Norway

The University of South-Eastern Norway invites applications for a PhD Research Fellowship in Data-Driven Methods and Sustainable Materials for Offshore Wind, based at the Department of Process, Energy and Environmental Technology, campus Porsgrunn. This full-time, three-year position offers a unique opportunity to contribute to the advancement of offshore wind energy, a cornerstone of the global green transition. The project addresses critical engineering challenges posed by the harsh marine environment, including component degradation, fatigue, corrosion, and erosion, with the aim of developing recyclable and durable materials, fast data-driven surrogate models, and lifecycle-conscious design strategies.

As a PhD candidate, you will join the REACT-Lab (Renewable Energy and Advanced Construction Technologies Laboratory) and the URGENT (USN Research Group in Energy and Environmental Technology) research group, collaborating with leading research institutes, industry partners, and international labs. The research focuses on bridging advanced computational mechanics with physical reality, moving beyond trial-and-error approaches by leveraging surrogate modeling techniques such as Kriging and Gaussian Processes. You will explore complex design spaces to identify resilient, resource-efficient material solutions, contributing to the North Sea’s ambitious 300 GW offshore wind target by 2050.

Key research areas include developing and training robust machine learning surrogates to replace computationally expensive high-fidelity simulations, formulating optimization frameworks that incorporate manufacturing capabilities and operational limits, and integrating material efficiency and lifecycle metrics into the design loop. The project offers access to advanced facilities and real-world validation, providing a stimulating environment for academic and professional growth.

Applicants must hold a master’s degree (120 ECTS) or equivalent in Civil Engineering, Mechanical Engineering, Applied Mathematics, or Computational Science, completed before the position commences. A solid theoretical foundation in computational mechanics, finite element analysis, numerical optimization, or materials science is required, along with competence in structural analysis, data-driven engineering design, optimization algorithms, surrogate modeling (Kriging, Gaussian Processes, Neural Networks), and scientific programming (Python, MATLAB). Admission to USN’s PhD program in Technology requires a weighted average grade of B or higher. English proficiency must be documented via TOEFL, IELTS, CAE/CPE, or PTE Academic, unless exempt by prior study or degree in English. Export license requirements must be met.

The position offers a competitive salary (NOK 550,800 per year, with possible promotion), attractive welfare benefits, and a statutory contribution to the state pension plan. The University provides an open and inclusive working environment, with opportunities for physical activities during working hours and support for employees with disabilities. The Academic Appointments Board will conduct an expert assessment of applicants, and interviews will be held for the most qualified candidates.

To apply, register your application and CV online via the Jobbnorge recruitment portal. Required documents include transcripts and diplomas, relevant certificates, a motivation letter, documentation of English proficiency, scientific publications and list, three references, and a copy of your master’s thesis if available. If your education is from outside Norway, apply for recognition from the Norwegian Directorate of Higher Education and Skills and attach the receipt. For further information, contact Assoc. Prof. Hadi Amlashi ([email protected]) or Department Head, Assoc. Prof. Ali Ghaderi ([email protected]).

Join a dynamic research team and help shape the future of offshore wind energy through innovative, data-driven, and sustainable engineering solutions.