Time-Domain Based Correlation and Validation
The PhD is hosted by the KU Leuven Noise and Vibration Research Group, which currently counts 90 researchers and is headed by Prof. Wim Desmet (https://www.kuleuven.be/wieiswie/en/person/00011973) and is part of the Mechanical Engineering Department, a vibrant environment of more than 300 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: https://www.mech.kuleuven.be/en/research/mod/about and our Linked.In page: https://www.linkedin.com/showcase/noise-&-vibration-research-group/.
This PhD focuses on time domain identification methods for modelling mechatronic systems. Standard methods focus on optimizing parameters by either minimizing the discrepancy between the time history of the measurement signal and the model output, or by optimizing towards a certain global criteria, i.e.,shifting time, transmission error in an ad hoc fashion. This often results in a fit based on the training data, and does not necessarily offer good predicting capabilities for operating regimes outside the regimes of the training set. Consequently,there is a clear need for novel identification strategies that not only optimize the parameters but also iterate on the equation structure and finally indicate which equations are responsible for the remaining model mismatch. An additional challenge is linked to incorporating different measurement sets and different operational conditions in a single identification step. The focus is on powertrains where the distributed flexibility is dominant and several non-linear aspects are present, i.e.,velocity-dependent stiffening effects, Coriolis forces due to bending loads,load-dependent bearing stiffness’s, etc. The result will be a pre-test,correlation and validation approach for non-linear systems.
As a PhD researcher your aim is to develop high-fidelity models with dedicated modular equation structure and to link them with novel identification strategies. As the space of unknown parameters is typically very large and the operating regimes include very non linear phenomena, a strong emphasis will be dedicated on computationally efficient strategies. You will deal with the trade-off between the accurate and rigorous modelling formulations, keeping in mind the final application goal of the model.
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 and performed above average in comparison to my peers.
- I am proficient in written and spoken English.
- I have some basic experience with first-principle modelling (1D/3D modelling), model identification (or numerical optimization in general) 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 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 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, 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 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 (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/living
To apply for this position, please follow the application tool and enclose:
- full CV – mandatory
- motivation letter – mandatory
- 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)
- proof of English proficiency (TOEFL, IELTS, …) - if available
- two reference letters - if available
- an English version of MSc or PhD thesis, or of a recent publication or assignment- if available
Please keep in mind that these documents must be in a pdf-format and can not be more than 4MB.
For more information about the vacancy, please contact Dr. Bert Pluymers by email –firstname.lastname@example.org. All applications should be done using the application tool. You can apply for this job no later than January 31, 2020 via the online application tool
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 diversiteit.HR@kuleuven.be.