Research Fellow (Digital Twin - Floating Offshore Wind Turbine)

Overview

This position focuses on developing an online framework to assess fatigue, structural integrity, and operational status of multiple floating offshore wind turbines (FOWT). Utilizing computationally efficient learning algorithms with prognostic features, the system supports prescriptive decision-making integrated within operation and maintenance plans. The candidate will collaborate within a multi-disciplinary team specializing in engineering analysis and design of floating offshore wind turbine structures, working closely with other research institutions across Singapore.

Key Duties

• Create computationally efficient learning algorithms tailored for real-time fatigue and structural integrity evaluations, incorporating predictive analytics methods.
• Develop prescriptive assessments for fatigue and structural health that align with operational and maintenance strategies.
• Coordinate research activities and progress updates with other groups forming the larger research team.

Qualifications

• Doctorate (PhD) in civil engineering, mechanical engineering, or a closely related field.
• Solid foundational understanding of fatigue and fracture mechanics, structural integrity evaluation, and data-driven machine learning techniques.
• Practical experience working in laboratory settings designing, executing, and instrumenting structural experiments.
• Excellent verbal and written communication skills.
• Willingness to accept a fixed-term contract arrangement.