Postdoctoral Position in Deep Learning Predictive Control for Industrial Processes

Ghent University


Postdoctoral position in deep learning predictive control for industrial processes


Research Group active on Artificial Intelligence for Mechatronic systems, Industrial robots and Industrial processes within the Faculty of Engineering at Ghent University is looking for outstanding applicants for postdoctoral positions.

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 on closing the loop from sensors to actuators to enable and advance on functionalities for 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 (

Job description

We are looking for a team member with a strong background in system identification and optimal control for dynamical systems. Starting date is as soon as possible, preferably 1st March 2020. For this position, we offer an internationally competitive salary that corresponds to the salary scales for Postdoctoral Research Fellows as established by the Flemish government.

You will work on a Moonshot project that has the overall aim to unlock and control the flexibility of the energy-intensive processes and of power-to-X to optimally reduce the CO2-emissions in a way that is best suited for the overall industrial and energy eco-system. In this project, innovative methods need to be researched and initiated to design and elaborate deep-learning-based techniques to optimally control the flexibility over multiple energy vectors, this according to different objective functions.

The fundamental research challenge within the project lies in the design of new techniques that combine modern data-driven methods with optimal control approaches to address the challenges faced by the energy-intensive industry. The specific research challenge lies in tackling the highly uncertain industrial system that is difficult to model and come up with deep learning based predictive control methodologies. Hybrid AI approaches will be furthermore researched by using reinforcement learning for policy refinement.

The research group on dynamics for electromechanical systems in which you will be embedded has extensive expertise in the research on hybrid AI methods for system identification/intelligence and optimal control that unlock functionalities to take AI to the real world.

The candidate will be expected to:

  • Perform research on deep learning optimal control for industrial processes. You will set out a technological basis for combining optimal control theory with reinforcement learning techniques.
  • You will develop methodologies and software (python, Matlab) for deep learning predictive control. You will present your research at conferences and in journals.  
  • You will coordinate activities related to the control of industrial processes and interact with PhD students
  • Participate to team meetings and external meetings with other research partners
  • You will look at opportunities to transfer knowledge towards mechatronic and robotic systems.
  • You will cooperate with researchers active within the research group and outside.
  • You will be embedded in an internationally competitive research group that has a strong focus on bringing artificial intelligence to the real world.

We offer to you:

  • The research group is situated in Ghent, a lively city at the heart of Europe (
  • The candidate will have access to state-of-the-art tools and facilities, a network of Flemish companies and the possibility to collaborate with other research groups.
  • The candidate will be directly embedded in an international research group of +20 people that work together as a team and will have the possibility to collaborate with many other people active at UGent and in Flanders.
  • Starting date: as soon as possible (1st March), but flexible.
  • You will be offered a contract of 1.5 years that can be extended.
  • You have a master of science degree in engineering, preferably in electromechanical or control engineering
  • You hold a PhD in electromechanical/control engineering.
  • You have extensive experience with the modelling and simulation of dynamical systems, preferably of industrial processes.
  • You have extensive experience with machine learning (supervised learning, reinforcement learning).
  • You have experience with system identification and nonlinear optimal control techniques for industrial processes.
  • You are motivated, creative and have a passion for academic research. You have excellent publication record, with publications in international peer-reviewed academic journals. You have excellent spoken and written academic English.

Profile of the candidate


How to apply

Please send your CV, containing a list of publications, a summary of past research, contact information of 2 or 3 referees, and a motivation letter to Prof. Guillaume Crevecoeur ( with subject ‘dControl position’.

In your application, please refer to