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Research Assistant in 3D Computer Vision for the Built Environment (Fixed Term)

University of Cambridge - Department of Engineering

Location: Cambridge
Salary: £33,002 to £35,608 per annum
Hours: Full Time
Contract Type: Fixed-Term/Contract
Placed On: 22nd September 2025
Closes: 6th October 2025
Job Ref: NM47348

A position is available in the Department of Engineering at the University of Cambridge for a Research Assistant in 3D Computer Vision for the Built Environment.

The post holder will be based in West Cambridge, Cambridgeshire, UK, and will join a dynamic research group at the forefront of developing advanced AI and computer vision tools for the built environment. The role will involve close collaboration with both national and international academic and industry partners, through the University's leading research centres, including the Laing O'Rourke Centre for Construction Engineering & Technology (LORC) and the Centre for Smart Infrastructure and Construction (CSIC).

The successful candidate will design and implement cutting-edge computer vision and geometric deep learning solutions for real-world applications in the built environment. Potential focus areas include automated point cloud processing, 3D reconstruction of buildings and infrastructure, shape completion, and surface reconstruction to support the creation of high-fidelity digital twins. Research outputs will contribute to practical challenges such as structural assessment, asset monitoring, and performance optimisation across diverse construction contexts.

Key responsibilities include:

  • Designing and developing novel AI-driven computer vision technologies (e.g., 3D reconstruction, digital twinning) for analysing and modelling the built environment.
  • Applying developed methods to real-world case studies using point cloud, image, and spatial datasets in collaboration with industry partners.
  • Coordinating with colleagues in Cambridge and liaising with national and international collaborators to ensure the research has strong real-world impact.
  • Disseminating results through technical reports, publications, and presentations at academic and industry forums.
  • Supporting junior researchers and contributing to the planning of future research projects.

This position offers the opportunity to be part of transformative, interdisciplinary research that combines digital innovation, civil engineering, and data science. The postholder will have the freedom to develop new ideas, methodologies, and tools within a supportive and collaborative team environment, with a focus on improving the efficiency, sustainability, and resilience of infrastructure projects.

Applicants are expected to have (or be close to obtaining) an undergraduate degree in data science or a closely related discipline. The successful candidate should have strong programming skills, proficiency in modern machine learning frameworks, and excellent written and spoken communication skills in English. Experience in applying AI/computer vision to 3D spatial data is desirable.

Salary range:

Research Assistant: £33,002-£35,608

Fixed-term: The funds for this post are available for 9 months in the first instance.

To apply online for this vacancy and to view further information about the role, please click the 'Apply' button above. 

Please ensure that you upload your Curriculum Vitae (CV) and a supporting letter in the Upload section of the online application. The supporting statement should cover your motivation for the post and a point-by-point account of how you meet each of the selection criteria.

This may include experience gained in employment, education, or during career breaks (such as time out to care for dependants). If you upload any additional documents which have not been requested, we will not be able to consider these as part of your application.

If you have any questions about this vacancy, please contact Dr Brian Sheil (bbs24@cam.ac.uk) for queries of a technical nature related to the role or csic-admin@eng.cam.ac.uk for queries related to the application process.

The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.

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