Research Assistant: AI-Enabled Inspection and Digital Twin for Critical Infrastructure (Transportation)

Department Department of Architecture and the Built Environment Location City Centre Campus (Millennium Point) Salary £38,050 to £44,131 per annum Fixed Term contract for 24 months Post Type Full Time Release Date 09 April 2026 Closing Date 23.59 hours BST on Thursday 30 April 2026 Reference ABCE26016

About Birmingham City University

At Birmingham City University, we are a diverse and inclusive learning community of over 31,400 students from more than 120 countries. We aim to become an exemplar anchor institution, creating and sharing knowledge for a better and more inclusive society. We are committed to providing a transformational educational experience, supporting world-class research, and fostering a collaborative and supportive working environment for our staff.

Recognised as one of the UK’s Top 250 employers (Financial Times & Statista), we pride ourselves on being a place where colleagues feel valued, supported, and able to grow their careers while contributing to the success of our students and communities.

Our student demographic reflects the rich cultural and ethnic diversity of Birmingham itself, with a significant proportion of students from minoritised ethnic backgrounds and the majority of our home students coming from the West Midlands. This diversity is a strength, and it calls for a workforce that is equipped to challenge deficit narratives and thinking — those assumptions that position students from underrepresented groups as lacking rather than recognising their assets, strengths and potential.

By embracing this perspective, we aim to create an environment where all students and colleagues can thrive, and where our work contributes positively to the social, cultural and economic life of Birmingham and beyond.

Role Summary

We are seeking a Research Assistant: AI-Enabled Inspection and Digital Twin for Critical Infrastructure (Transportation) to join our Department of Architecture and the Built Environment, School of Architecture, Built Environment, Computing and Engineering (ABCE), contributing to internationally funded research developing AI-driven inspection and digital twin systems for transportation infrastructure.

In this role, you will play a central role in BCU’s contribution to the STRUCTURE project – a European project developing AI-enabled autonomous inspection and digital twin platforms for critical transportation infrastructure, including bridges, railways, and airport runways. Key responsibilities include AI model development for automated defect detection, sensor data fusion, and digital twin integration specific to transportation assets, working closely with a European consortium of universities, technology companies, infrastructure operators, and national highways authorities to ensure services are efficient, compliant, and aligned to University priorities.

Key Responsibilities

• Develop and apply AI and machine learning algorithms for automated defect detection and structural condition assessment of bridges using UAV-collected inspection data
• Process and analyse aerial inspection datasets from bridge structures, developing robust algorithms capable of identifying defects, deterioration, and structural anomalies
• Contribute to the development and validation of digital twin models for bridge assets, integrating AI-derived condition assessments for predictive maintenance and asset management applications
• Collaborate with consortium partners on the integration of AI analytics and digital twin outputs into operational inspection and maintenance workflows for bridge infrastructure owners and operators
• Produce peer-reviewed journal papers, conference presentations, technical reports, and dissemination materials aligned with STRUCTURE project obligations
• Engage with end-users and infrastructure operators to ensure AI and digital twin outputs are aligned with operational maintenance workflows and regulatory requirements

Essential Requirements

• A minimum 2:1 undergraduate degree in Computer Science, Artificial Intelligence, Software Engineering, Civil Engineering, Digital Built Environment, or a closely related discipline
• Experience with AI and machine learning techniques for image/sensor data analysis, computer vision, or structural/geospatial data processing
• Proficiency in Python and/or other relevant programming languages for data processing, model training, and integration
• Understanding of data management principles for structured and unstructured datasets from inspection or monitoring systems
• Strong written and verbal communication skills, with the ability to present technical findings to both academic and non-technical audiences
• Ability to work independently and collaboratively within an international multi-partner research consortium, managing time effectively to meet project milestones

Desirable Requirements

• MSc or PhD in Artificial Intelligence, Data Science, Digital Built Environment, Civil/Structural Engineering, or a closely related discipline
• Familiarity with UAV/drone inspection technologies, remote sensing, or non-destructive evaluation (NDE) methods applied to infrastructure
• Knowledge of digital twin platforms, Building Information Modelling (BIM), or asset lifecycle management systems
• Understanding of transportation infrastructure types (bridges, rail, road, airfield pavements) and their inspection and maintenance requirements
• Experience in an applied or industry-facing research environment such as a funded project, KTP, or industrial placement
• A track record of academic publication or evidence of research dissemination

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 or Dr Vahid Javidroozi at Vahid.Javidroozi@bcu.ac.uk.

Why not explore our campuses using our interactive map: Interactive Map | Birmingham City University

Why work for us

• 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.

Visa Sponsorship

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.

Further Details

Job Description

Email details to a friend

Apply Online

Share

View All Vacancies