PhD Position Data-enabled systems and control co-design for large-scale wind turbines

Updated: 4 months ago
Deadline: 30 Jun 2023

13 May 2023
Job Information

Delft University of Technology (TU Delft)
Research Field

Researcher Profile

First Stage Researcher (R1)

Application Deadline

30 Jun 2023 - 21:59 (UTC)
Type of Contract

Job Status

Not Applicable
Is the job funded through the EU Research Framework Programme?

Not funded by an EU programme
Is the Job related to staff position within a Research Infrastructure?


Offer Description

In the last decades, the classical control theory has proven its effectiveness in terms of analysis and control (design) methodologies. Control theory has been a key enabler in the realization of complex systems. However, increasing system complexity leads to an increasingly indirect relationship between linear to practically meaningful performance. Moreover, the intricate requirements for system performance complicate controller design through the sole use of the classical control theory. Synergizing established fundamental control with promising data-enabled machine-learning techniques could effectively solve these present-day design challenges.

You will develop algorithms to effectuate efficient data-enabled systems and control co-design approaches. Therefore, you will tightly synergize the established control theory with novel data-enabled techniques from the fields of machine learning (ML) and artificial intelligence (AI). This allows for the design and efficient calibration of the system and controller in unison.

The algorithms you develop will be applied to wind turbines in simulation and experimentally on lab-scale wind tunnel set-ups. The application area is highly relevant, as wind turbines see a rapid increase in system complexity. Next-generation large-scale wind turbines are growing with increasing performance demands to satisfy the net-zero emission targets. This size increase leads to greater complexity through dynamic interactions. The exponential growth of data from wind turbines motivates the development and application of novel co-design techniques to achieve next-level performance, ultimately lowering the costs of renewable energy.

Specific Requirements

This position is perfect for you if you possess profound knowledge of system modeling, system analysis, and (classical) control engineering, and when you have experience with or special interest in ML/AI techniques.

You will have ample space to display your auto-didactic skills and independently conduct ground-breaking research. You have a strong research-oriented attitude, good communication skills, and the ability to transfer knowledge and effectively present your challenges and results. Also, you are willing to grow as a positive (graduate) student supervisor. Working from elsewhere is permitted, however, there is a requirement to be present at least four days per week at the TU Delft faculty.

You also have:

  • An MSc in systems and control (control engineering), mechatronics, mechanical engineering, aeroelastics, machine learning, or a related field.
  • Excellent programming skills in MATLAB/Simulink.
  • Excellent command of the English language.

Make sure to apply when this position does spark excitement in you. If you do not tick all the boxes but are in possession of a profound understanding of control engineering, we’d definitely like to get to know you!

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 .

Additional Information

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 € 2541 per month in the first year to € 3247 in the fourth year. 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 sport memberships, and a monthly work costs contribution. Flexible work schedules can be arranged.

For international applicants, TU Delft has the Coming to Delft Service . This service provides information for new international employees to help you prepare the relocation and to settle in the Netherlands. The Coming to Delft Service offers a Dual Career Programme for partners and they organise events to expand your (social) network.

Selection process

Please apply by 30 June 2023 via the application button and upload:

1) a detailed curriculum vitae that explicitly states your educational record, and (if applicable) working experience, recent major achievements, list of publications,

2) a separate motivation letter stating why the proposed research topic interests you,

3) the names of three persons who could be contacted for a reference and any other information that might be relevant to your application,

4) (Draft) MSc graduation thesis.

A pre-employment screening can be part of the selection procedure.

You can apply online. We will not process applications sent by email and/or post.

Please do not contact us for unsolicited services.

Additional comments

The PhD project is co-supervised by Sebastiaan Mulders (assistant professor) and Jens Kober (associate professor). For more information about this vacancy, please contact Sebastiaan Mulders, e-mail: .

For more information about the selection procedure, you can contact Irina Bruckner, HR Advisor, email: .

Website for additional job details

Work Location(s)
Number of offers available
Delft University of Technology
Postal Code
2628 CD
Mekelweg 2

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Mekelweg 2
Postal Code

2628 CD

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