University of Bergen
2 weeks ago
PhD Research Fellow in Data-Driven Computational Mechanics for Offshore Wind Energy University of Bergen in Norway
Degree Level
PhD
Field of study
Computer Science
Funding
Fixed-term PhD Research Fellow position for 3 years, with a possible 4th year depending on qualifications and teaching needs. Salary is NOK 593,700 gross annually in the state salary scale, with further increases by length of service. Includes enrolment in the Norwegian Public Service Pension Fund and welfare benefits. The position is financed by the EU/ERC Consolidator Grant project DATA-DRIVEN OFFSHORE.
Deadline
Sep 28, 2026
Country
Norway
University
University of Bergen

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About this position
University of Bergen (UiB) is advertising a PhD Research Fellow in Data-Driven Computational Mechanics for Offshore Wind Energy at the Geophysical Institute (GFI), linked to the Bergen Offshore Wind Centre (BOW) and the EU-funded ERC Consolidator Grant project DATA-DRIVEN OFFSHORE.
The project focuses on data-driven computational mechanics for the aerohydroelastic analysis of offshore wind turbines. The research aims to move from data-starved to data-rich computational approaches, where loads, boundary conditions, and constitutive models may be partially or fully replaced by experimental data. The work is expected to contribute to high-impact international publications and to connect closely with ongoing research at BOW and GFI.
Academic background: applicants must have a master's degree (or have submitted the thesis before the deadline) in engineering, informatics, mathematics, or physics. The degree must be awarded before employment. Strong programming skills (e.g., Fortran or C++) are required. Experience with the finite element method, numerical optimization, and high-performance computing is an advantage. Excellent written and oral English is required, and applicants must meet the PhD programme enrolment requirements at UiB.
Funding and terms: the position is a fixed-term PhD fellowship for 3 years, with a possible 4th year depending on qualifications and teaching needs. Salary is NOK 593,700 gross per year, with pension and welfare benefits. The fellowship is financed by the EU/ERC project DATA-DRIVEN OFFSHORE.
How to apply: submit the application via Jobbnorge with a motivation letter, a detailed qualification statement addressing all listed requirements and advantages, CV, transcripts and diplomas, proof of English proficiency if required, references, and a publication list. Two referees must be named, including the main master's thesis supervisor. Deadline: 28 September 2026.
Funding details
Fixed-term PhD Research Fellow position for 3 years, with a possible 4th year depending on qualifications and teaching needs. Salary is NOK 593,700 gross annually in the state salary scale, with further increases by length of service. Includes enrolment in the Norwegian Public Service Pension Fund and welfare benefits. The position is financed by the EU/ERC Consolidator Grant project DATA-DRIVEN OFFSHORE.
What's required
Applicants must hold a master's degree or equivalent education in engineering, informatics, mathematics or physics, or have submitted the master's thesis before the application deadline; the master's degree must be awarded before employment. Programming skills such as Fortran or C++ are required. Competence in the finite element method, numerical optimization, and high-performance computing is advantageous. Applicants must work independently and in a structured manner, collaborate well, and have excellent written and oral English skills. Admission/enrolment requirements for the PhD programme at the University of Bergen must be satisfied.
How to apply
Apply through Jobbnorge and upload the application with all appendices. Include a motivation statement, detailed qualification statement addressing all requirements and advantages, CV, transcripts and diplomas, proof of English proficiency if required, references, and a publication list. Provide contact information for two referees, including the main master's thesis advisor.
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