Stage vacatures in Barendrecht

Challenge: Developing novel representation and foundation model for architectural engineering subjects.

Change: Advancing human-in-the-loop systems of architectural engineering knowledge tasks, with a focus on enhanced digital-human agency in design, engineering and construction coordination.

Impact: Enhancing adaptability and scalability of AI models in building engineering.

Job description

We are seeking a highly motivated PhD candidate to pioneer the integration of architectural knowledge and logic directly into the latent manifold of Generative AI. This position operates at the cutting edge of AI and the Built Environment, challenging you to architect a native Multimodal Foundation Model for Architectural Engineering designed for "Constraint-to-BIM (Building Information Modelling)" synthesis. You will investigate how deep neural networks can internalize complex building dynamics (e.g., structural load paths, material thermodynamics) and regulatory logic (e.g., zoning envelopes) as native languages, facilitating rigorous, carbon-centric decision-making. If you are driven to transcend generic, task-agnostic generation and advance frontier AI toward structurally and functionally viable design, join us in defining this new scientific paradigm.

Your core research will target three novel frontiers: (1) heterogeneous input encoding, where you will develop architectures to unify disparate modalities into a coherent embedding space; (2) causal chain-of-thought, engineering mechanisms for the model to manage long-horizon dependencies in construction sequencing and system-level planning; and (3) constraint-aware latent reasoning, innovating tokenization strategies that semantically bind geometric primitives with performance constraints to ensure "construction-valid" generation. You will apply parameter-efficient fine-Tuning (e.g., low-rank adaptation) to an open-source Multimodal Foundation Model (MMLM) for domain-specific adaptation, combining it with novel pretraining objectives (e.g., topology-preserving loss, consistency-based self-supervision) to overcome engineering data scarcity and enable autonomous reasoning for tasks such as structural integrity, HVAC routing, and climate-adaptive design.

You will work within an interdisciplinary ecosystem of domain experts and stakeholders from industry and the public sector. A critical component of your work will be establishing rigorous evaluation protocols to probe the model's physics-consistency and logic-adherence, moving the field beyond standard perceptual metrics. Your contributions will define the state-of-the-art through publications in leading AI and built-environment venues, the release of open benchmarks for architectural reasoning, and the formulation of methodological guidelines for reliable domain-specific foundation models. Ultimately, your research will deliver a unified native foundation model, providing the multi-level disciplinary intelligence essential for the early-stage development of sustainable, high-performance buildings.

Requirements

• You hold an MSc in Computer Science, Artificial Intelligence, Data Science or Architectural Engineering (with strong computational focus), demonstrating a solid portfolio at the intersection of Deep Learning and geometric/physical data.
• You have a keen interest and/or experience in large-scale model architectures, specifically focusing on self-supervised learning, latent space alignment, or multimodal representation learning.
• You have solid programming skills (e.g. Python) and are familiar with modern ML frameworks such as PyTorch or TensorFlow.
• You are motivated to work with complex and heterogeneous AEC (Architecture, Engineering, and Construction) data.
• You possess hands-on experience in at least one of the following frontier areas: Geometric Deep Learning (GNNs, 3D-CNNs), Computer Vision, or Vision-Language Models (VLMs).
• You have excellent scientific communication skills in English and a driven ambition to publish high-impact research in top-tier AI and Built Environment venues.
• You thrive in bridging disciplines, capable of working translating complex problems into potential solutions and collaborating effectively with domain experts and industry stakeholders.

TU Delft (Delft University of Technology)

Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context.

At TU Delft we embrace diversity as one of our core values and we actively engage to be a university where you feel at home and can flourish. We value different perspectives and qualities. We believe this makes our work more innovative, the TU Delft community more vibrant and the world more just. Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale. That is why we invite you to apply. Your application will receive fair consideration.

Challenge. Change. Impact!

Faculty Architecture & the Built Environment

The Faculty of Architecture and the Built Environment has a leading role in education and research worldwide. The driving force behind the faculty's success is its robust research profile combined with the energy and creativity of its student body and academic community. It is buzzing with energy from early in the morning until late at night, with four thousand people studying, working, designing, conducting research and acquiring and disseminating knowledge. Our faculty has a strong focus on 'design-oriented research', which has given it a top position in world rankings.

Staff and students are working to improve the built environment with the help of a broad set of disciplines, including architectural design, urban planning, building technology, social sciences, process management, and geo-information science. The faculty works closely with other faculties, universities, private parties, and the public sector, and has an extensive network in the Netherlands as well as internationally.

Click here to go to the website of the Faculty of Architecture and the Built Environment.

Conditions of employment

Doctoral candidates will be offered a 4-year period of employment in principle, but in the form of 2 employment contracts. An initial 1,5 year contract with an official go/no go progress assessment within 15 months. Followed by an additional contract for the remaining 2,5 years assuming everything goes well and performance requirements are met.

The TU Delft offers a customisable compensation package, discounts on health insurance, and a monthly work costs contribution. Flexible work schedules can be arranged.

. This service provides information for new international employees to help you prepare the relocation and to settle in the Netherlands. The Coming to Delft Service offers a for partners and they organise events to expand your (social) network.

Additional information

Are you interested in this vacancy? Please apply before 25 January 2026 (local Dutch time + 2 hrs) via the application button and upload:

• Motivation letter (maximum 1 page) addressing your interests and describing how your experience and plans fit with the position.
• Detailed CV.
• Undergraduate and graduate transcripts.
• The names of two references, with contact information (letters not required at this stage).

Please address your application to Dr.ir. Pei-Yu Wu, Assistant Professor at the Digital Technology Section at the Department of Architectural Engineering and Technology.

The initial interviews will take place in mid-Februay 2026.

Doing a PhD at TU Delft requires English proficiency at a certain level to ensure that the candidate is able to communicate and interact well, participate in English-taught Doctoral Education courses, and write scientific articles and a final thesis. For more details please check the Graduate Schools Admission Requirements.

• You can apply online. We will not process applications sent by email and/or post.
• As part of knowledge security, TU Delft conducts a risk assessment during the recruitment of personnel. We do this, among other things, to prevent the unwanted transfer of sensitive knowledge and technology. The assessment is based on information provided by the candidates themselves, such as their motivation letter and CV, and takes place at the final stages of the selection process. When the outcome of the assessment is negative, the candidate will be informed. The processing of personal data in the context of the risk assessment is carried out on the legal basis of the GDPR: performing a public task in the public interest. You can find more information about this assessment on our website about knowledge security.
• Please do not contact us for unsolicited services.