Shaping Offshore Wind with Physics-Informed ML (Postdoc)
1000scholars
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Benefits offered by this job
Job summary
The University of Bergen invites applications for a 3-year postdoctoral research fellow position in Physics-informed Machine Learning for offshore wind. The project unites nine partners from six EU/EEA countries to deliver real-time reliability assessment and predictive maintenance through integrated sensing, modelling, and digital frameworks.
Starting 1 January 2027, the role offers strong collaboration with leading researchers, opportunities to present at international meetings, and a
Qualifications
- PhD degree completed or submitted for assessment; PhD must be awarded.
- High-quality journal papers in relevant topics.
- Interdisciplinary research experience is advantageous.
- Ability to work independently and in a structured, collaborative way.
Responsibilities
- Develop data-driven surrogate models for real-time reconstruction and forward simulations.
- Create numerical algorithms for physics reconstruction from sparse data.
- Implement assimilation pipelines combining physics and surrogate models.
- Collaborate with project teams and participate in project activities.
- Produce project deliverables and contribute to dissemination.
Skills
Education
Job description
The University of Bergen invites applications for a 3-year postdoctoral research fellow position in Physics-informed Machine Learning for offshore wind. The project unites nine partners from six EU/EEA countries to deliver real-time reliability assessment and predictive maintenance through integrated sensing, modelling, and digital frameworks.
Starting 1 January 2027, the role offers strong collaboration with leading researchers, opportunities to present at international meetings, and a
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