PhD Student

Last application date
Sep 30, 2023 00:00
TW08 - Department of Electromechanical, Systems and Metal Engineering
Limited duration
M.Sc. degree in mechanical, electrical, energy and/or control engineering, or related engineering fields
Occupancy rate
Vacancy type
Research staff

Job description

We are seeking a highly motivated and talented PhD researcher in the field of control, electrical and mechanical engineering of energy systems. Our goal is to advance wind turbine and wind farm control systems so that they learn from interactions with the wind; this to improve annual energy production and reduce loads for lifetime.
You will work on a 4-years cutting-edge Horizon Europe research project that pursues smart and integrated wind farm controllers that interact with digital twins. This doctoral research will seek for dedicated model-based strategies that incorporate both data-driven and physics-based modeling techniques. By learning from real wind data, we seek to close the uncertainties that arise in physics-based models. These hybrid physics-based data-driven models will then act as a digital twin of the real wind turbine and will be embedded in a model predictive controller. You are responsible to build such advanced models and controllers to effectively improve energy production and reduce loads. You will investigate their effectiveness on simulations as well as on historic and operational wind turbine/farm data. A particular focus lies in the validation of the developed digital twins and controllers, as well as the integration with other partners into open-source toolchains. Your research will be conducted under the supervision of Prof. Guillaume Crevecoeur (system dynamics, design and control) and Prof. Lieven Vandevelde ((wind) energy systems).
You have a Master's degree in a relevant field, such as mechanical and/or electrical engineering, control and automation, energy, or mechatronics engineering. Ideally, candidates have experience in advanced control strategies as well as in energy systems, and will be able to demonstrate a strong understanding of these concepts before starting this position.
If you are passionate about conducting cutting-edge research in the field of energy systems, we encourage you to apply for this exciting opportunity.

You will be responsible for:

  • conducting research into AI-based wind turbine and wind farm control
  • developing strategies for wind turbines that synergistically include data-driven and physics-based models
  • embedding these models in time-critical controllers for wind turbines.
  • integrating digital twins and controllers on a wind farm level towards increasing the annual energy production and the lifetime.
  • analyzing historic wind turbine and wind farm data, as well as making validations of models/controls with field tests (sensors, controls, processing, etc.)
  • presenting your research at conferences and in high-impact journals
  • cooperating with researchers active within the Horizon Europe research project, and interacting with researchers within the research group.

Our offer:

  • A 4 years period doctoral position.
  • An internationally competitive salary that corresponds to the salary scales for Doctoral Research Fellows as established by the Flemish government.
  • Access to state-of-the-art tools and facilities, a network of Flemish companies active in the manufacturing industry, researchers working on energy, and the possibility to collaborate with other research groups.
  • The time to apply and improve your knowledge and skills on state-of-the-art in wind energy systems, machine learning, system identification, numerical optimization, nonlinear optimal control.
  • Starting date: 1 December 2023 (at the earliest)

About us
This research fits within a Horizon Europe project. This research is supervised by Prof. Guillaume Crevecoeur working on the modelling, control and design of physical dynamic systems (, and Prof. Lieven Vandevelde active in (wind) energy systems ( We are part of the department of Electromechanical, Systems and Metal Engineering within the Faculty of Engineering of Ghent University ( Ghent University is a top 100 university worldwide and one of the major universities in Belgium, with more than 44000 students and 15000 staff members. Our campus is situated in in Ghent, a lively city at the heart of Europe ( Our research group is also associated with MIRO (Machines, Intelligence, Robots and ElectrOmechanical systems), the core lab from Ghent University active within the Flanders Make (, the strategic research center for the Flemish manufacturing industry. The candidate will be directly embedded in an international research group, working together as a team and will have the possibility to collaborate with many other people active within Ghent University and within Flanders.

Job profile

We look for a highly motivated and talented individual with at least some background in mechanical engineering, having knowledge in wind energy applications and has modeling and control experience. You are quick-witted, have an appetite for the theoretical and experimental, and willing to apply and/or improve your programming skills.

  • You hold an M.Sc. degree in mechanical, electrical, energy and/or control engineering, or related engineering fields.
  • You have proven experience with the control, modelling and simulation of (wind) energy systems.
  • You have proven experience in Python and/or MATLAB.
  • You have experience in or understanding of wind energy systems and software.
  • You have a team player mindset, a strong personality and work in a result-oriented manner.
  • You are creative and willing to work in a multidisciplinary context.
  • You are proficient in oral and written English and have strong communication skills.
  • You are willing to extend your network and able to talk on technical matters.

How to apply

Send your CV, containing 1 or more references and a motivation letter to Guillaume Crevecoeur ( including ‘WIND PHD’ in the email subject before Saturday 30 September 2023. If you pass the pre-selection, you will receive further instructions on the selection process and will be invited for an online job interview.