Postdoc Prognostics Wind Turbines

X-ray Enhanced Prognostics for Composite Structures

Job description

Offshore wind energy is a cornerstone of Europe’s transition to a carbon-neutral energy system. As offshore wind capacity in the Netherlands rapidly expands and existing assets age, there is an urgent need for cost-effective and sustainable maintenance strategies. Wind turbine blades are among the most failure-prone components due to their composite construction, large size, and exposure to harsh cyclic loading. Current inspection-based maintenance approaches often lead to conservative lifetime estimates, premature blade replacement, and significant economic and material losses.

This postdoctoral position is essential to enabling predictive maintenance and circular end-of-life strategies for offshore wind turbine blades. The role focuses on developing advanced prognostic models that can reliably predict the Remaining Useful Life (RUL) of wind turbine blades' components. By transforming diagnostic inspection data into actionable predictions, the work will directly contribute to reducing downtime, lowering operational costs, and improving the sustainability of offshore wind operations.

You will develop, implement, and validate prognostic models for composite blade structures, with a focus on integrating diagnostic information from advanced Digital X-ray inspections into physics-informed prognostic frameworks. Key responsibilities include uncertainty quantification and management in RUL predictions, model validation using experimental data, and contributing to scientific publications and project deliverables.

The position is based at TU Delft and is part of a close collaboration with Spect

X, an industrial partner specializing in Digital X-ray diagnostics.

This role is embedded within the Intelligent Systems Prognostics (iSP) Group in the Faculty of Aerospace Engineering at Delft University of Technology. The iSP Group is dedicated to advancing prognostics and health management (PHM) methodologies for engineering systems and structures, supporting efficient and reliable operations and maintenance.

• A PhD degree in engineering, mathematics, or a related field, with a strong background in prognostics for engineering systems and structures. Experience with composite materials is considered an advantage.
• Proficiency in programming languages such as Python, C, and/or R.
• Demonstrated experience in experimental research, including structural health monitoring (SHM) techniques.
• Strong analytical and critical-thinking skills, with the ability to independently define research directions, and lead key technical aspects of the project.
• Ability to work effectively within a multidisciplinary project team while taking ownership of individual research objectives and deliverables.
• Excellent proficiency in English, both written and oral, with the ability to communicate research outcomes clearly to academic and industrial stakeholders.

The selected candidate is expected to actively contribute to a dynamic and collaborative research environment within the Intelligent Systems Prognostics (iSP) for Operations & Maintenance Group, Department of Aerospace Structures and Materials, Faculty of Aerospace Engineering at Delft University of Technology.

Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context.

At TU Delft we embrace diversity as one of our core values and we actively engage to be a university where you feel at home and can flourish. We value different perspectives and qualities. We believe this makes our work more innovative, the TU Delft community more vibrant and the world more just. Together, we imagine, invent and create solutions using technology to…