PhD Position in Self-Learning Intelligent Monitoring of Cyber-Physical System Fleet

Catholic University of Leuven

The KU Leuven Mecha(tro)nic System Dynamics division (LMSD) is searching for a PhD candidate to join its team and to take up a H2020 Marie Sklodowska Curie ESR fellowship within the MOIRA ITN project.


  • The PhD candidate will work on machine-learning and artificial-intelligence methods for self-learning and self-monitoring cyber-physical systems. A framework based on novelty detection will be established using dynamically updated clustering methodologies, capturing the transition of the system between multiple steady and time-varying operating modes. Moreover, self-organizing model methods will be investigated and further developed. ESR2 will establish a procedure in order to perform comparisons of identical or possibly similar cyber-physical systems (drivetrains, vehicles, machines) using similarity measures, in order to identify and monitor abnormal phenomena, such as wear, failures and noise. The developed methodologies and algorithms will first be tested and evaluated on simulated data and on two dedicated similar but not identical laboratory drivetrains, in order to quantify the rate of false alarms and missed detections. The final methodology evaluation will be performed on real industrial cases.
  • As a PhD researcher your aim will be to develop advanced unsupervised self-learning methods based on streaming data for fleet monitoring.
  • The research is hosted by the KU Leuven Noise and Vibration Research Group – as part of the Mecha(tro)nic System Dynamics division (LMSD), which currently counts >100 researchers ( The research group has a long track record of combining excellent fundamental academic research with industrially relevant applications, leading to dissemination in both highly ranked academic journals as well as on industrial fora. More information on the research group can be found on the website: and our linkedIn page: . The PhD will be co-supervised by Prof. Konstantinos Gryllias.


If you recognize yourself in the story below, then you have the profile that fits the project and the research group.
  • I have a master degree in engineering, physics or mathematics.
  • I am proficient in written and spoken English.
  • During my courses or prior professional activities, I have gathered experience with signal processing, machine-learning, artificial-intelligence, machine dynamics modeling and design, data-acquisition and I have a profound interest in these topics. 
  • As PhD researcher of the KU Leuven Noise and Vibration Research Group I perform research in a structured and scientifically sound manner. I read technical papers, understand the nuances between different theories and implement and improve methodologies myself. 
  • I work goal-oriented and have a getting-things-done attitude, always with scientific rigor.
  • In frequent reporting, varying between weekly to monthly, I show the results that I have obtained and I give a well-founded interpretation of those results. I iterate on my work and my approach based on the feedback of my supervisors which steer the direction of my research.
  • I feel comfortable to work as a team member and I am eager to share my results to inspire and being inspired by my colleagues.
  • I value being part of a large research group which is well connected to the machine and transportation industry and I am eager to learn how academic research can be linked to industrial innovation roadmaps.
  • During my PhD I want to grow towards following up the project that I am involved in and representing the research group on project meetings or conferences. I see these events as an occasion to disseminate my work to an audience of international experts and research colleagues, and to learn about the larger context of my research and the research project.


  • A remuneration package in line with Marie Sklodowska Curie ITN regulations, which is competitive with industry standards in Belgium, a country with a high quality of life and excellent health care system.
  • An opportunity to pursue a PhD in Mechanical Engineering, in a stimulating and ambitious research environment, with 3 years funding within the MOIRA ITN project.
  • An opportunity to work within a challenging European research project with leading industry players across Europe. 
  • A stay in a vibrant environment in the hearth of Europe. The university is located in Leuven, a town of approximately 100000 inhabitants, located close to Brussels (25km), and 20 minutes by train from Brussels International Airport. This strategic positioning and the strong presence of the university, international research centers, and industry, lead to a safe town with high quality of life, welcome to non-Dutch speaking people and with ample opportunities for social and sport activities. The mixture of cultures and research fields are some of the ingredients making the university of Leuven the most innovative university in Europe ( Further information can be found on the website of the university:


To apply for this position, please follow the application tool and enclose:
1) Full CV – mandatory
2) Motivation letter – mandatory
3) Full list of credits and grades of both BSc and MSc degrees (as well as their transcription to English if possible) – mandatory (when you haven’t finished your degree yet, just provide us with the partial list of already available credits and grades)
4) Proof of English proficiency (TOEFL, IELTS, …) - if available
5) Two reference letters - if available
6) An English version of MSc or PhD thesis, or of a recent publication or assignment - if available
For more information please contact Prof. Konstantinos Gryllias ( by mail and mention MOIRA_ESR2 in the title.
You can apply for this job no later than March 02, 2021 via the
KU Leuven seeks to foster an environment where all talents can flourish, regardless of gender, age, cultural background, nationality or impairments. If you have any questions relating to accessibility or support, please contact us at
  • Employment percentage: Voltijds
  • Location: Leuven
  • Apply before: March 2, 2021
  • Tags: Ingenieurswetenschappen