Company
neoBIM GmbH
Location
Remote, Germany
Employment type
Full-time
Primary category
Construction Engineering
Posted date
1 Apr 2026
Valid through
31 May 2026
neoBIM is a well-funded software start-up rethinking how architects design buildings through intelligent BIM tooling. As part of our applied research agenda, we are opening a thesis-aligned research position at the intersection of generative AI and computational architectural design.
Research Area
The broad focus of this position is the application of Generative Flow Networks (GFlowNets) to architectural design problems — in particular, the generation of diverse, constraint-aware spatial layouts. The concrete research question and scope will be developed together with the candidate based on their background and academic requirements.
Review relevant literature on GFlowNets and generative approaches to architectural layout generation
Define and refine a research question in collaboration with the team
Implement and experiment with GFlowNet-based models on spatial design tasks
Design reward functions encoding architectural constraints and objectives
Evaluate outputs in terms of diversity, feasibility, and constraint compliance
Compare against suitable baseline generative approaches
Document findings as a research report or thesis
Must have
Strong Python and PyTorch skills, as well as GIT
Background in machine learning; familiarity with RL or probabilistic generative models is a plus
Ability to work independently on open-ended research tasks
Comfortable reading and engaging with recent ML papers
Nice to have
Prior exposure to GFlowNets (Bengio et al.)
Interest in architectural design or spatial reasoning
Experience with graph neural networks or geometric deep learning
Familiarity with graph-based data representations or knowledge graphs
A concrete, novel research problem with real-world grounding in AEC
Close collaboration with our AI and product team
Dedicated thesis mentorship from our AI team
Potential for publication or continued collaboration post-thesis
Flexible remote setup
For any questions regarding this position, feel free to contact Felix directly via phone or messenger at +49 176 95422094.