Research Assistant: AI-Enabled Digital Twin for Critical Infrastructure Inspection
Department: Department of Architecture and the Built Environment
Location: City Centre Campus (Millennium Point)
Salary: £38,050 to £44,131 per annum
Contract: Fixed Term 36 months
Post Type: Full Time
Release Date: 09 April 2026
Closing Date: 23.59 hours BST on Thursday 30 April 2026
Reference: ABCE26018
Role Summary
We are seeking a Research Assistant to join the Department of Architecture and the Built Environment, School of Architecture, Built Environment, Computing and Engineering (ABCE). In this role you will contribute to internationally funded research projects HERD: STRUCTURE and MariSens, focusing on AI‑enabled UAV inspection and digital twin development for critical infrastructure such as bridges, offshore wind structures, harbour infrastructure and subsea assets.
Key Responsibilities
* Develop and implement AI and machine‑learning algorithms for automated defect detection and condition assessment using UAV‑collected inspection data.
* Develop digital twin frameworks that integrate AI‑derived inspection outputs for transportation infrastructure and offshore/coastal maritime assets.
* Coordinate and work with research associates across the STRUCTURE and MariSens projects, providing cross‑programme technical leadership and ensuring alignment between UAV inspection and digital twin research activities.
* Collaborate with consortium partners across the UK and Europe on platform integration, system validation and translation of research outputs into operational inspection workflows.
* Produce peer‑reviewed journal papers, conference presentations, technical reports and other dissemination outputs.
* Engage with infrastructure operators, regulatory bodies and maintenance service providers to align research outputs with real‑world operational needs.
Qualifications
* A minimum 2:1 undergraduate degree in Computer Science, Artificial Intelligence, Software Engineering, Civil Engineering, Digital Built Environment or a closely related discipline.
* Demonstrable experience with AI and machine‑learning frameworks for computer vision, sensor data analysis or structural/geospatial data processing.
* Proficiency in Python and/or other relevant programming languages for data processing, model development and system integration.
* Strong understanding of data management, including structured and unstructured datasets from sensor or inspection systems.
* Excellent written and verbal communication skills, with the ability to present complex technical findings to academic and industry audiences.
* Ability to manage workload independently, meet project milestones and collaborate effectively within a large international research consortium.
* MSc or PhD in Artificial Intelligence, Data Science, Digital Built Environment, Infrastructure Engineering or a closely related discipline.
* Experience with digital twin platforms, Building Information Modeling (BIM) or asset lifecycle management systems.
* Familiarity with UAV/drone inspection systems or autonomous aerial data collection for infrastructure applications.
* Knowledge of civil engineering, transportation infrastructure or offshore/marine structures and their inspection and maintenance requirements.
* Understanding of IoT platforms, connected sensor networks or real‑time data streaming systems relevant to infrastructure monitoring.
* Experience in a collaborative or industry‑facing research environment such as a funded research project, KTP or industrial placement.
* A track record of academic publication or research dissemination.
Benefits
* Work–life balance – Generous leave and hybrid working (role dependent).
* Career development – Opportunities to grow, develop and progress your career.
* Reward and wellbeing – Competitive pay, pension, wellbeing support and staff benefits.
* Inclusive culture – A supportive, diverse environment where everyone belongs.
Further Information
If you are excited by the opportunity to help shape the future of the School of Architecture, Built Environment, Computing and Engineering, we would love to hear from you.
For an informal discussion about the role, please contact Dr Saeed Talebi at Saeed.Talebi@bcu.ac.uk.
This role may be eligible for sponsorship under the Skilled Worker visa route, subject to meeting the relevant criteria. For further information, please visit: https://www.gov.uk/skilled-worker-visa
Equality, Diversity & Inclusion
We are committed to equality, diversity and inclusion and to an environment that supports lawful free speech and academic freedom. We will continuously review and improve our policies, practices, and procedures to ensure that we are promoting these in all aspects of our operations. We believe that by working together, combining our many different backgrounds and life experiences, we will empower each other to reach our full potential.
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