博士职位 风电场流动控制的实验验证

The rapid development of large offshore wind farms is essential for the transition towards a sustainable energy system. However, as wind turbines are installed increasingly close together, they interact through turbulent wind wakes. These wakes reduce the energy production of downstream turbines and can increase structural loading, creating a major challenge for the efficient and reliable operation of large wind farms.

A novel approach developed within our research group, known as Helix, aims to mitigate these wake losses by actively manipulating the wake using individual blade pitch control. While promising results have been obtained, the effectiveness of Helix-and other advanced wake-mixing strategies-strongly depends on the accuracy of the wind farm models used to design and evaluate these control strategies. Improving the predictive capability of these models therefore remains a key scientific challenge.

In this PhD project, you will develop and apply data-fusion methods that combine physics-based wind farm models with wind tunnel and field data. A particular focus will be on exploiting the extensive experimental data generated within the HKN project, including measurements from wind-tunnel experiments and full-scale offshore wind turbines. These data will be used to improve and calibrate wind farm models, quantify their uncertainties, and experimentally assess the performance of Helix and potentially other wake-mixing and wind farm control strategies.

The project will bridge wind farm aerodynamics, advanced control, system identification, filtering, and data-driven modelling, with a strong emphasis on combining physical knowledge with measurements rather than relying on purely data-driven approaches. The ultimate goal is to develop more accurate and reliable models and methodologies for the design, validation, and deployment of advanced wind farm control strategies.

Teaching activities are part of your PhD trajectory and may include, for example: supervising workgroups or lab sessions, assisting in courses, or mentoring BSc and MSc students. While teaching will not be your main responsibility, it offers valuable experience that supports your development and prepares you for future academic or professional roles. Teaching activities will not exceed 20% of your total appointment, averaged over the course of your PhD.

Job Requirements

The successful candidate has the following qualifications:

• An MSc. degree in systems and control, fluid dynamics wind energy, aeroelastics, mechatronics, applied mathematics, mechanical engineering, or a related field.
• The capacity to communicate effectively with peers, students and stakeholders in the application field.
• Good programming skills are a plus: MATLAB, Python, Git.
• Fluency in English.
• An open personality and good communication skills in written and spoken English.

Conditions of Employment

Doctoral candidates will be offered a 4-year period of employment in principle, but in the form of 2 employment contracts. An initial 1,5 year contract with an official go/no go progress assessment within 15 months. Followed by an additional contract for the remaining 2,5 years assuming everything goes well and performance requirements are met.

Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from €3204 - €4051 gross per month, from the first year to the fourth year based on a fulltime contract (38 hours), plus 8% holiday allowance and an end-of-year bonus of 8.3%.

As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills.

The TU Delft offers a customisable compensation package, discounts on health insurance, and a monthly work costs contribution. Flexible work schedules can be arranged.

Will you need to relocate to the Netherlands for this job? TU Delft is committed to make your move as smooth as possible! The HR unit, Coming to Delft Service, offers information on their website to help you prepare your relocation. In addition, Coming to Delft Service organises events to help you settle in the Netherlands, and expand your (social) network in Delft. A Dual Career Programme is available, to support your accompanying partner with their job search in the Netherlands.

Additional Information

For more information about this vacancy, please contact prof. Jan-Willem van Wingerden, [email protected].

For more information about the application procedure, please contact Mr. Giedo Kocken, HR advisor, [email protected].

Application Procedure

Are you interested in this vacancy? Please apply no later than 31 October 2026 via the application button and upload the following documents:

• CV
• Motivational letter
• (Draft) Master thesis
• If the applicants are selected for an interview, they will be asked to provide contact details of at least two referees with their consent

You can address your application to prof. Jan-Willem van Wingerden.

Doing a PhD at TU Delft requires English proficiency at a certain level to ensure that the candidate is able to communicate and interact well, participate in English-taught Doctoral Education courses, and write scientific articles and a final thesis. For more details please check the Graduate Schools Admission Requirements.

Please note:

• You can apply online. We will not process applications sent by email and/or post.
• As part of knowledge security, TU Delft conducts a risk assessment during the recruitment of personnel. We do this, among other things, to prevent the unwanted transfer of sensitive knowledge and technology. The assessment is based on information provided by the candidates themselves, such as their motivation letter and CV, and takes place at the final stages of the selection process. When the outcome of the assessment is negative, the candidate will be informed. The processing of personal data in the context of the risk assessment is carried out on the legal basis of the GDPR: performing a public task in the public interest. You can find more information about this assessment on our website about knowledge security.
• Please do not contact us for unsolicited services.