(ref. BAP-2026-301)
Laatst aangepast: 17/05/26
The M-Group at KU Leuven Bruges Campus is an interdisciplinary research team focusing on intelligent and dependable mechatronic systems, combining research expertise from the departments of Computer Science, Electrical Engineering and Mechanical Engineering. One of the key research tracks focusses on the application of Artificial Intelligence and Machine Learning in real-world industrial settings on the one hand. The objective of the proposed PhD positions is to investigate how foundation models can be leveraged for generative design of integrated mechanical assemblies, with a focus on the embodiment stage. The successful candidate will be offered to opportunity to pursue a PhD in Computer Science at KU Leuven, and will also be embedded within the Declarative Languages and Artificial Intelligence (DTAI) lab (https://dtai.cs.kuleuven.be), which pursues excellence in an explicit and synergistic combination of fundamental and applied research on machine learning and artificial intelligence. Doctoral training is provided in the framework of the Leuven Arenberg Doctoral School (https://set.kuleuven.be/phd). The PhD will be supervised by Prof. Mathias Verbeke.
Context
Designing a mechatronic system requires navigating a long chain of decisions that runs from initial concept all the way through to manufacturable detail. In practice, roughly half of the total engineering effort accumulates in the stretch between embodiment and detailed design: the phase where a rough concept must be turned into a geometry that respects tolerances, integration constraints, material limits, and downstream manufacturing requirements. Current tools offer little support here. Optimization-driven generative design can produce structurally efficient shapes, but remains a workflow-heavy, expert-only process. Current foundation models can assist with early ideation, but lacks the quantitative fidelity needed to produce designs that are actually buildable. What is missing is an intelligent agent that can take a human concept and progressively develop it into a validated, constraint-compliant embodiment, while keeping the designer in control throughout.
Project
This PhD position is part of the GENIMA project, a collaborative research project supported by Flanders Make, the strategic research center of the manufacturing industry. The objective of the project is to develop a designer-centric, physics-grounded, agentic framework for mechatronic design. The project advances a single human concept through multiple iterations toward realistically detailed and validated designs, combining data-efficient AI with proven optimization methods. This PhD contributes to the embodiment generation agent at the core of the framework: the component responsible for translating high-level design intent into structured, buildable concepts.
The central research challenge of this PhD is to make foundation models useful and reliable in the mechatronic design domain, where data is scarce, constraints are strict, and outputs must be physically plausible and manufacturable. You will adapt pretrained vision-language and CAD-specific models to this domain using data-efficient fine-tuning techniques such as LoRA, supplemented by domain-specific data augmentation strategies including parametric CAD variation and rule-based synthesis of design variants. Alongside this, you will develop a constraint enforcement mechanism that formalises domain-specific design rules (e.g. mechanical tolerances) and integrates them directly into the generation process so that non-compliant designs are penalised and steered toward viable alternatives. The entire process is designed to remain under designer control: you will develop interaction protocols that allow engineers to steer the agent through textual feedback or constraint overrides.
The methods developed will be validated on two industrial demonstrators in high-precision mechanics and opto-mechanical system design.
We are seeking a highly motivated, enthusiastic, passionate, and communicative researcher, with a proactive and creative attitude who is eager to explore innovative solutions. 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's degree in Computer Science, Artificial Intelligence, Mechanical Engineering, Mathematical Engineering or a related field and performed well 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 experience with machine/deep learning, foundation models and agentic AI, and can demonstrate a strong affinity with these fields. Prior experience with generative design is a plus.
- I am proficient in Python and am familiar with data science and machine/deep learning toolkits. Furthermore, I am familiar with the main concepts in mechanical product design (e.g., CAD).
- As a PhD researcher at KU Leuven, 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 research group which is well connected to the mechatronics 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 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.
We encourage candidates from diverse backgrounds and experiences to apply, as we believe that different perspectives contribute to better research and innovation.
Application Instructions for the PhD vacancy
To apply for this position, please use the online application tool and ensure that you submit the following documents in a single PDF file:
- Motivation Letter: A letter (maximum 1 A4 page) addressing your strengths and qualifications in relation to the project.
- Complete Academic CV: A detailed CV including information about your education, current position, work experience (if any), employment gaps (if any), interests, extracurricular activities, international experiences, and projects demonstrating your programming/software skills, background knowledge relative to the project and level of expertise.
- List of Publications: If applicable, provide a list of your publications, including DOIs. Please do not include PDFs of the publications.
- Copies of Diplomas: Include copies of your BSc and MSc degrees.
- Transcript of Records: Provide transcripts for your BSc and MSc degrees. If you have not yet completed your Master's degree, include your available credits and scores, as well as a list of courses you are taking in the upcoming semester.
- English Summary of Master Thesis: A summary of your master thesis in English (maximum 1 A4 page, or 2 pages max when including a figure).
- Proof of English Language Proficiency: Documentation demonstrating your proficiency in English (TOEFL, IELTS, …), if available.
- Reference Letter or Contact Details: A reference letter or the contact information for one reference who can provide a recommendation letter upon request.
The position will be hosted within the collaborative and internationally oriented research environment at KU Leuven, one of the world's leading universities (ranked among the top 100 globally). Founded in 1425, KU Leuven has been a center of learning for nearly six centuries and is Belgium’s highest-ranked university, as well as one of the oldest and most renowned universities in Europe. KU Leuven provides a truly international experience, high-quality education, world-class research, and cutting-edge innovation, having topped Reuters' ranking of Europe's most innovative universities for four consecutive years.
We offer:
- A fully funded 4-year PhD scholarship, with a remuneration package competitive with industry standards in Belgium, a country with a high quality of life and excellent health care system.
- 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.
- Opportunities to collaborate in groundbreaking research and participate in international conferences.
- Access to state-of-the-art infrastructure and a range of university benefits (health insurance, etc.).
- A dynamic, passionate team of fellow PhD students and test engineers.
As a PhD candidate, you will be based at KU Leuven’s Bruges Campus (https://www.kuleuven.be/english/bruges), as part of a dynamic and interdisciplinary team of AI researchers, with access to state-of-the-art lab facilities to experimentally validate your findings in close collaboration with industrial partners.
The successful candidate will be encouraged to present their research at international conferences and national events, with a strong emphasis on publishing high-quality conference papers and journal articles. They will benefit from our robust international research and industrial network, which is actively involved in this project.
KU Leuven Campus Bruges, located in the magnificent medieval city of Bruges in West Flanders, offers a vibrant academic setting in close proximity to a network of companies. The campus features newly established labs to support both educational and research needs.
DTAI Lab at the Department of Computer Science
M-Group at KU Leuven Bruges Campus
You can apply for this job no later than June 18, 2026 via the online application tool
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.
Heb je een vraag over de online sollicitatieprocedure? Raadpleeg onze veelgestelde vragen of stuur een e-mail naar [email protected]
av_timer Tewerkstellingspercentage: Voltijds
location_city Locatie: Brugge
timer Solliciteren tot en met:
18/06/2026 23:59 CET
bookmarks Tags: Computerwetenschappen, Wiskunde, Werktuigkunde, Elektrotechniek, Industriële Ingenieurswetenschappen, Ingenieurswetenschappen
