The KU Leuven Mecha(tro)nic System Dynamics division (LMSD) and the Campus Diepenbeek Polymer Processing & Engineering (PPE) groups are searching for a Doctoral Candidate to join its team to work in the challenging Horizon Europe MSCA project APRIORI: Active PRoduct-to-Process LearnIng fOR Improving Critical Components Performance.
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Project
- This PhD is part of the Horizon Europe MSCA doctoral network APRIORI (Active PRoduct-to-Process LearnIng fOR Improving Critical Components Performance). APRIORI is an international consortium of high-profile universities, research institutions and companies located in Belgium, the Netherlands, Denmark and Slovenia. The European manufacturing sector is experiencing and will continue experience a transition, characterized by the exponential growth of additive manufacturing, the 4th industrial revolution (Industry 4.0) and an increasing demand of customization of the manufactured products. The ambition of the APRIORI training network is to fully support this evolution by training 10 doctoral candidates (DCs) and future innovators to deal with two key technical challenges within the manufacturing sector: the uncertainty induced by the production process and the increasing complexity of the manufactured goods characterized by the critical parts or components. This will be achieved by developing the skills and new technologies that will enable for the first time the development of a unique integrated product design strategy that will drastically improve the performance of critical parts or components under uncertainties.
- As DC5 in the APRIORI training network you will develop and exploit digital twins for quality control of the injection moulding process, aiming at critical products within the automotive sector. You will set up detailed injection moulding simulations and you will design a dedicated mould to generate a large dataset, linking specified settings, measurements and final product quality (geometry, but also strength, stiffness and dynamic properties). You will create a data driven Digital Twin, using the detailed simulations to steer the optimization and to enrich the data set where needed. A transfer learning approach will be considered for the simulation to real knowledge transfer. Additionally the possibility of creating a hybrid model, combining machine learning and physical model will be considered. Finally, you will develop a condition monitoring system, using real time data, supported by the digital twin, to steer and improve the production process when deviations apply, by providing optimised operating settings.
- The research is hosted by the Mecha(tro)nic System Dynamics division (LMSD), which currently counts >100 researchers and is part of the department of mechanical engineering of KU Leuven. 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: https://www.mech.kuleuven.be/en/research/mod/about and our linkedIn page: https://www.linkedin.com/showcase/lmsd-kuleuven/.
Profile
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, obtained no longer than four years ago, and performed above average in comparison to my peers.
- I am proficient in written and spoken English.
- I haven’t had residence or main activities in Belgium for more than 12 months in the last 3 years.
- During my courses or prior professional activities, I have gathered some basic experience with the physical principles of injection moulding and the related measurement and numerical modelling techniques, and/or I have a profound interest in these topics.
- As a 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.
- Based on interactions and discussions with my supervisors and the colleagues in my team, I set up and update a plan of approach for the upcoming 1 to 3 months to work towards my research goals. I work with a sufficient degree of independence to follow my plan and achieve the goals. I indicate timely when deviations of the plan are required, if goals cannot be met or if I want to discuss intermediate results or issues.
- 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.
Offer
- A remuneration package competitive with industry standards in Belgium, a country with a high quality of life and excellent health care system. EU Researcher allowances will be used to cover both the employee's as the employer's mandatory charges.
- An opportunity to pursue a PhD in Mechanical Engineering, typically a 4 year trajectory, in a stimulating and ambitious research environment.
- Ample occasions to develop yourself in a scientific and/or an industrial direction. Besides opportunities offered by the research group, further doctoral training for PhD candidates is provided in the framework of the KU Leuven Arenberg Doctoral School (https://set.kuleuven.be/phd), known for its strong focus on both future scientists and scientifically trained professionals who will valorise their doctoral expertise and competences in a non-academic context. More information on the training opportunities can be found on the following link: https://set.kuleuven.be/phd/dopl/whytraining.
- A stay in a vibrant environment in the hearth of Europe. The university has campuses across Flanders. Your research will be mainly carried out at Campus Leuven, with regular visits to Campus Diepenbeek (https://www.kuleuven.be/english/campuses/diepenbeek-campus/about/index.html) for the experimental activities. Leuven is 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 (https://nieuws.kuleuven.be/en/content/2018/ku-leuven-once-again-tops-reuters-ranking-of-europes-most-innovative-universities). Further information can be found on the website of the university: https://www.kuleuven.be/english/life-at-ku-leuven/
Interested?
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. dr. ir. Konstantinos Gryllias (konstantinos.gryllias@kuleuven.be) or Prof. dr. Elke Deckers (elke.deckers@kuleuven.be).
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