KU LEUVEN
Development of agentic CAE based mechanical design methods
KU LEUVEN, Sauk Trail Beach, Wisconsin, United States
Job Details
Organisation/Company: KU LEUVEN Research Field Engineering » Mechanical engineering Researcher Profile First Stage Researcher (R1) Country Belgium Application Deadline 30 Jan 2026 - 23:59 (UTC) Type of Contract: To be defined Job Status: Full-time Offer Starting Date: 1 Apr 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Reference Number BAP-2025-728 Is the Job related to staff position within a Research Infrastructure? No
Offer Description The KU Leuven Mecha(tro)nic System Dynamics division (LMSD) is searching for a research engineer to join its team to work in the field of agentic design methods for mechanical systems. This Ph.D. is part of a research project aiming to develop novel approaches for the computational design of mechanical systems, moving away from strict optimization methods into an agentic framework. On the one hand computational design optimization methods (topology optimization, genetic algorithms for component selection, …) can offer a powerful framework to select the best design, but often struggle in practical applicability due to the required knowledge from designers on optimization. On the other hand, AI methods like GPTs allow to come up with conceptual designs, but lack accuracy to come up with real implementable designs. In this research track you will explore novel agentic methods combined with computer aided engineering (CAE) and computational design optimization to achieve effective design support for detailed mechanical design. This will require researching state‑of‑the‑art design optimization methods and AI based approaches to steer and augment these optimization schemes, to ensure that the obtained designs are consistent with concrete design requirements (strenght, eigenfrequencies, …). Besides the methodological research, the development of relevant demonstration cases will play a key role in this work. This will ultimately lead to an improved design framework to assist mechanical engineers in coming up with the best possible designs more rapidly.
Eligibility criteria
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.
During my courses or prior professional activities, I have gathered some basic experience with numerical modelling methods and optimization methods.
I have notions about multibody and finite‑element simulation.
I am proficient in programming basic methods in MATLAB and/or Python.
As a PhD researcher of the KU Leuven Mecha(tro)nic System Dynamics 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 I show the results that I have obtained and I give a well‑foundated 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.
Benefits
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, welcoming 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-re… ). Further information can be found on the website of the university: https://www.kuleuven.be/english/living.
Application Process
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
For more information please contact prof. Frank Naets (frank.naets@kuleuven.be) by mail and mention [GENIMA Vacancy] in the title.
#J-18808-Ljbffr
Offer Description The KU Leuven Mecha(tro)nic System Dynamics division (LMSD) is searching for a research engineer to join its team to work in the field of agentic design methods for mechanical systems. This Ph.D. is part of a research project aiming to develop novel approaches for the computational design of mechanical systems, moving away from strict optimization methods into an agentic framework. On the one hand computational design optimization methods (topology optimization, genetic algorithms for component selection, …) can offer a powerful framework to select the best design, but often struggle in practical applicability due to the required knowledge from designers on optimization. On the other hand, AI methods like GPTs allow to come up with conceptual designs, but lack accuracy to come up with real implementable designs. In this research track you will explore novel agentic methods combined with computer aided engineering (CAE) and computational design optimization to achieve effective design support for detailed mechanical design. This will require researching state‑of‑the‑art design optimization methods and AI based approaches to steer and augment these optimization schemes, to ensure that the obtained designs are consistent with concrete design requirements (strenght, eigenfrequencies, …). Besides the methodological research, the development of relevant demonstration cases will play a key role in this work. This will ultimately lead to an improved design framework to assist mechanical engineers in coming up with the best possible designs more rapidly.
Eligibility criteria
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.
During my courses or prior professional activities, I have gathered some basic experience with numerical modelling methods and optimization methods.
I have notions about multibody and finite‑element simulation.
I am proficient in programming basic methods in MATLAB and/or Python.
As a PhD researcher of the KU Leuven Mecha(tro)nic System Dynamics 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 I show the results that I have obtained and I give a well‑foundated 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.
Benefits
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, welcoming 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-re… ). Further information can be found on the website of the university: https://www.kuleuven.be/english/living.
Application Process
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
For more information please contact prof. Frank Naets (frank.naets@kuleuven.be) by mail and mention [GENIMA Vacancy] in the title.
#J-18808-Ljbffr