Research Fellow (Digital Twin - FOWT)

Interested applicants are invited to apply directly at the NUS Career Portal. Please note your application will only be processed if you apply via NUS Career Portal.

NUS Career Portal link: https://careers.nus.edu.sg/job/Research-Fellow-%28Digital-Twin-FOWT%29/32459-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

The research aims to develop an online framework for assessing fatigue, structural integrity, and operability of multiple floating offshore wind turbines, supported by computationally efficient learning algorithms with predictive (prognostic) capabilities. The system enables prescriptive decision-making that can be integrated with operation and maintenance strategies. The research staff will work in a multi-disciplinary team on the engineering analysis and design of the floating offshore wind turbine supporting structures, with close collaboration with members from other research institutes in Singapore.

He/ she will be required to:
- Develop computationally efficient learning algorithm adaptable for online fatigue and integrity assessment, which includes prognosis approach for predictive analytics.
- Develop prescriptive fatigue and integrity assessments integrable with operation/maintenance strategy.
- Coordinate research progress with other research teams in the entire research team

Job Requirements

. Applicants should have a PhD degree in civil or mechanical engineering or related disciplines
. Possess fundamental knowledge in fatigue and fracture, structural integrity assessments and data driven machine learning algorithms.
. Has laboratory experience in designing, conducting, and instrumenting structures.
. Strong written and spoken communications.
. Open to fixed-term contract