Doctoral student in AI 3D city modelling

We invite applications for a Doctoral student position in applied mathematics and machine learning for urban 3D reconstruction, within the Digital Twin Cities Centre (DTCC). The project aims to create analysis‑ready, topology‑correct 3D city models from multi‑modal geospatial data. The position is hosted at the Department of Mathematical Sciences at Chalmers University of Technology and the University of Gothenburg. You will work at the interface of rigorous mathematics, modern AI, and research‑grade software development, with results integrated into the DTCC Platform and validated on real city data in collaboration with DTCC partners. About us  The department of Mathematical Sciences has about 200 employees and is the largest department of mathematics in Sweden. The department has three scientific divisions: Algebra and Geometry, Analysis and Probability Theory, and Applied Mathematics and Statistics and conducts successful research in pure and applied mathematics and mathematical statistics in a wide range of research areas. We have an international environment with frequent exchanges with other universities around the world. The department provides a friendly, creative, and supportive atmosphere with a steady flow of international guests. We strive to offer an environment where you can combine world-leading research and teaching with a good work-life balance.  At the division of Applied Mathematics and Statistics we conduct research within the theory and implementation of biomathematics, biostatistics, spatial modeling, differential equations, Bayesian inference, large-scale computational methods, bioinformatics, data science, machine learning, optimisation, numerical methods. Please read more about the position and our department on our dedicated webpage. About the research project    City digital twins require more than visually plausible models: they require analysis‑ready geometry for simulation and decision support. This PhD project develops methods to generate LOD3 urban surface meshes from heterogeneous geospatial data such as LiDAR point clouds, aerial orthophotos, street‑level imagery, and map/cadastral information. A central requirement is topological correctness—watertight, manifold meshes without self‑intersections and with consistent connectivity—together with quantifiable accuracy and scalability to city‑wide deployment. The research combines machine learning with geometry processing and mathematical analysis. You will develop learning‑based models (e.g., sparse 3D CNNs and related architectures) for multi‑modal interpretation and reconstruction, and design topology‑aware meshing and refinement algorithms that support hierarchical levels of detail. The theoretical component includes convergence and error bounds for refinement, conditions for topological validity, robustness to noisy measurements, and stability/generalization guarantees for learning‑based mesh generation. Software will be developed with research‑grade engineering practices and released as open‑source components in the DTCC Platform, enabling direct use in applications such as wind comfort (CFD), urban heat and solar studies, flood and noise simulations, infrastructure management, and AR/VR visualization. Who we are looking for The following requirements are mandatory: • To qualify as a Doctoral student, you must have a Master's degree (masterexamen) of 120 credits or a Master’s degree (magisterexamen) of 60 credits* in Mathematics with at least one course in differential geometry. Alternatively, you expect to complete such a degree by September 1, 2026. • You will need strong written and verbal communication skills in English  • A successful candidate must have strong coding skills. • Personal competences in accordance with the requirements profile including specification (e.g. social skills, meaning that you enjoy collaborating with others)  *for students with an education earned outside of Sweden, a 4-year Bachelor’s degree is accepted.  The following experience will strengthen your application:  Read more about this at Chalmers website What you will do • Take courses at an advanced level within the Graduate school of Mathematics or Applied Mathematics and Statistics • Develop your own scientific concepts and communicate the results of your research verbally and in writing  • The position generally also includes teaching on Chalmers' undergraduate level or performing other duties corresponding to 20 percent of working hours  Contract terms   • The Doctoral student position is fully funded from start.  • The position is a fixed-term appointment of four years, with the possibility to teach up to 20%, which extends the position up to five years.  • A starting salary of 34,550 SEK per month (valid from May 25, 2025).  • Doctoral studies require physical presence throughout the entire study period. A valid residence permit must be presented by the study start date; otherwise the admission may be withdrawn.  What we offer  • As a Doctoral student at Chalmers, you are an employee and enjoy all employee benefits. Read more about  working at Chalmers  and our benefits for employees.  • A dynamic and inspiring working environment in the coastal city of Gothenburg.  • Read more about Sweden’s generous parental leave, subsidized day care, free schools, healthcare etc at Move To Gothenburg.  Chalmers is dedicated to improving gender balance and actively works with equality projects, such as the GENIE Initiative for gender equality and excellence. We celebrate diversity and consider equality and inclusion as fundamental aspects of all our activities.  If Swedish is not your native language, Chalmers offers Swedish courses to help you settle in. Find more general information about doctoral studies at Chalmers here.   Application procedure    Read more and apply at Chalmers website We welcome your application no later than February 23, 2026    For questions, please contact:   Professor Anders Logg (main supervisor) Dr Irina Pettersson (head of unit, Applied Mathematics and Statistics) We look forward to your application!  *** Chalmers declines to consider all offers of further announcement publishing or other types of support for the recruiting process in connection with this position. ***