PhD Studentship: Multimodal 3D Generative AI for Urban Modelling and Digital Twin Applications

Primary supervisor - Dr Cheng Wang

We are seeking an outstanding PhD candidate to join our research group at the School of Computing Sciences, working at the frontier of 3D computer vision, multimodal learning, and generative AI. This project aims to advance how artificial intelligence perceives, reconstructs, and synthesizes urban environments, integrating geometric reasoning with modern generative models to support the creation of intelligent and dynamic digital twins. 

Research Focus 

The PhD will explore novel algorithms and applications for representing, understanding, and generating urban-scale 3D contents, to build realistic, editable, and semantically rich 3D models. Specific objectives may include: 

• Developing robust 3D reconstruction pipelines for urban scenes from multi-view imagery, video, or sparse sensor data 
• Investigating multimodal 3D generative models that integrate visual, language, and spatial cues 
• Leveraging neural scene representations for digital twin applications, enabling interactive editing, simulation, and predictive modelling 

The project combines fundamental research in representation learning and generative models with applied innovation in urban modelling and digital technologies. The PhD project will produce high-impact research to publish in leading venues, including SIGGRAPH, CVPR, and ICCV. 

Environment and Supervision 

You will join a vibrant research environment within the School of Computing Sciences at UEA, collaborating closely with experts in computer vision, computer graphics, and AI. The project is part of a broader initiative on multimodal 3D learning, involving collaborations with both academic and industrial partners. The supervisor will support the student in undertaking at least two industrial internships during the 3-year PhD programme, with opportunities to collaborate with leading companies such as Epic Games, Meta, and Adobe, as well as partners in urban analytics. 

Candidate Profile 

The ideal candidate will hold (or be about to obtain) a bachelor’s or master’s degree in computer science, computer engineering, applied mathematics, or a related discipline. 

For informal enquiries, please contact Dr Cheng Wang at Cheng.C.Wang@uea.ac.uk

Entry requirements

First class in bachelor degree or a master degree in Computer Science/ Computer Engineering/ Applied Maths/ Physics.

Mode of study

Full-time

Start date

1 October 2026

Funding

This PhD project is in a competition for a Faculty of Science funded studentship. Funding is available to UK applicants and comprises ‘home’ tuition fees and an annual stipend for 3 years.

Closing Date 

10/12/2025

To apply for this role, please click on the 'Apply' button above.

Advert information