The KU Leuven Mecha(tro)nic System Dynamics (LMSD) and the Campus De Nayer are searching for a research engineer to join its team.Website unit
Project
The recruited doctoral candidate will perform research based on the following objectives:
Develop a physics-based baseline time domain model for vibro-acoustic components using FEM/BEM and reduced-order modelling techniques.
Fuse sparse microphone or accelerometer data with model prediction enabling robust real time field reconstruction. Within this objective, techniques such as dynamic reduced order models, Kalman filtering and Physics Informed neural operators/networks will/can be employed.
Exploit the reconstructed field to design a calibration (neural) model that bridges the gap between the physics-based prediction and the corrected field, ensuring physical interpretability and data adaptivity. Operator inference strategies can/will be employed to infer the properties of such a model.
Extend the methods to a parametric calibration model through new material properties, new geometric configurations and sound sources through sophisticated interpolation strategies and/or transfer learning, enabling parametric response evaluation across vehicle assemblies.
The developed strategies will be employed for the auralization of an existing electric vehicle.
The PhD is supervised by prof. Dionysios Panagiotopoulos (https://www.kuleuven.be/wieiswie/nl/person/00120151) from the KU Leuven LMSD division. 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/.
The required funding has already been secured through the starting funds of Prof. Panagiotopoulos, ensuring a fully funded four-year PhD trajectory. Nevertheless, candidates with exceptionally strong profiles will be strongly encouraged to make use of the initial phase of the project to apply for an individual PhD fellowship through the Research Foundation – Flanders (FWO), further strengthening their academic track record and research independence.
The main work location of the recruited candidate will be Campus De Nayer (https://www.kuleuven.be/campussen/campus-de-nayer), with the possibility to use a flex desk in Leuven/Heverlee. The candidate will have access to exceptional vibration and acoustics lab facilities and the new Automotive Test Center facilities (https://thomasmore.my360.be/3d/campus-de-nayer/n001/).
The candidate will become part of the LMSD with a legacy on novel noise and vibration technique development. The candidate will frequently interact with researchers in other campuses (e.g. campus Heverlee, campus Diepenbeek) who work on noise and vibration research topics, while it is expected to contribute to the establishment and further development of noise and vibration research activities at Campus De Nayer. In this context, the candidate is expected to demonstrate a strong sense of initiative, ownership, and responsibility, and to actively support the growth and consolidation of the local research activities and collaborations.
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 and performed above average in comparison to my peers. I am not in possession of a doctoral degree at the date of recruitment.
I am proficient in written and spoken English.
During my courses or prior professional activities, I have gathered some basic experience with the basic physical principles of acoustics and the related numerical modelling techniques, such as the Finite Element Method (FEM), Boundary Element Method (BEM), and/or with the basic principles of Machine Learning and/or Model Order Reduction or I have a profound interest in these topics.
During my courses or prior professional activities, I have gathered experience in vibro-acoustic measurement techniques or I have a profound interest in this direction.
I demonstrate a strong sense of initiative and responsibility, while also being an effective and collaborative team player.
As a PhD researcher of the KU Leuven LMSD division 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 be 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 representing the research group on 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.
Offer
The possibility to study in a dynamic and international research environment in collaboration with industries and prominent universities worldwide.
You will receive a monthly salary of a Belgian phd scholarship, i.e. https://www.kuleuven.be/personeel/jobsite/en/phd/phd-information
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.
Interested?
Follow the KU Leuven job 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 your MSc or PhD thesis, or of a recent publication or assignment - if available
For more information please contact Dionysios Panagiotopoulos (Dionysios.Panagiotopoulos@kuleuven.be) by mail.
KU Leuven strives for an inclusive, respectful and socially safe environment. We embrace diversity among individuals and groups as an asset. Open dialogue and differences in perspective are essential for an ambitious research and educational environment. In our commitment to equal opportunity, we recognize the consequences of historical inequalities. We do not accept any form of discrimination based on, but not limited to, gender identity and expression, sexual orientation, age, ethnic or national background, skin colour, religious and philosophical diversity, neurodivergence, employment disability, health, or socioeconomic status. For questions about accessibility or support offered, we are happy to assist you at this email address.
Fields: Acoustics, Vehicle Dynamics, Machine Learning, Engineering Physics
