PhD Student

PhD researcher - modeling and control of airborne wind energy system

Research Group working on mechatronic, robotic and electromechanical systems within the Faculty of Engineering at Ghent University (campus Ghent) is looking for outstanding applicants for a doctoral position.

About us
The candidate will be directly embedded in an international research group that work together as a team and will have the possibility to collaborate with many other people active at Ghent University and within Flanders. The research group performs fundamental and applied research to advance and enable the functionalities and capabilities of mechatronic, robotic and industrial processes. The research group is associated to Flanders Make and is situated in Ghent, a lively city at the heart of Europe (https://visit.gent.be/en/HOME ).

Job description
We are looking for a team member with a strong background in system modelling, machine learning, optimization and optimal control for dynamical systems. Starting date is flexible. For this position, we offer an internationally competitive salary that corresponds to the salary scales for Doctoral Research Fellows as established by the Flemish government.
You will work on the BORNE project that has the overall aim to further explore the capabilities of airborne wind energy by means of high fidelity modeling frameworks. In this project, innovative methods need to be researched and initiated to combine modelling and optimal control strategies for airborne wind energy systems.
The fundamental research challenge within the project lies in the design of new high-fidelity modelling methods to address the challenges faced by the aerial systems, namely unsteady flows and flexible structures, and strategies to combine the former methods. Your specific research challenge lies in the development of optimal control strategies which make use of high-fidelity simulation methods by means of machine learning methodologies.
The research group on dynamics for electromechanical systems in which you will be embedded has extensive expertise in the system modeling and control of real world electromechanical, mechatronic and robotic systems.

The candidate will be expected to:

• Perform research on combining optimal control theory with high fidelity modelling techniques by means of machine learning methodologies.
• You will develop methodologies and software (python, Matlab) for machine learning, modelling and control.
• You will present your research at conferences and in journals.
• You will cooperate with researchers active within the research group and outside.
• You will be contribute to the teaching related to modelling, optimization and control

We offer:

• A 4 years period doctoral position
• The candidate will have access to state-of-the-art tools and facilities, a network of Flemish companies active in the manufacturing industry, and the possibility to collaborate with other research groups.
• The appropriate time to become experienced with machine learning, modelling, optimization and optimal control methods, in order to further develop them and apply them later on.
• The research group is situated in Ghent, a lively city at the heart of Europe (https://visit.gent.be/en/HOME).
• Starting date: flexible.

Profile of the candidate

• You hold a M.Sc. in electromechanical engineering
• You have experience in or understanding of electromechanical/mechatronic/robotic systems.
• You have experience in or understanding of artificial intelligence, modelling of dynamical systems, optimal control.
• You have a team player mindset, a strong personality and work in a result-oriented manner.
• You are creative, 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.

Send your CV, containing 2 or 3 references, and a motivation letter to Jolan Wauters ([email protected] ) and Prof. Guillaume Crevecoeur ([email protected] ) via e-mail with subject 'PhD Vacancy BORNE' before 30th September 2021.