2 PhD Positions in Life Extension of Civil Engineering Structures
Role highlights
Full Time
Permanent
Intern
On-site
These two PhD positions focus on advancing life extension techniques for civil engineering structures such as bridges and buildings. Candidates should hold a relevant Master’s degree in civil or mechanical engineering and possess strong competencies in computational methods. Key technical skills include computational mechanics, uncertainty quantification, and machine learning. The research emphasizes developing next-generation tools integrating automated structural health monitoring through robotics and multi-modal data acquisition. Candidates will work on cyber-physical sensing systems designed to train physics-informed machine learning models for accurately estimating structural loads from traffic, wind, and other factors. The projects require a solid understanding of structural engineering principles combined with expertise in AI-driven data analysis and sensor technologies. Applicants are expected to propose a focused research plan addressing a sub-topic within this domain, demonstrating their ability to integrate computational and experimental approaches. The positions are based at Aarhus University, Denmark, within the Civil and Architectural Engineering program, offering a multidisciplinary environment that bridges civil engineering, robotics, and data science. This opportunity suits candidates aiming to contribute to innovative solutions for infrastructure durability and sustainability through advanced computational and sensing methodologies.
About the role
Role Summary
- 2 PhD fellowships at Graduate School of Technical Sciences, Aarhus University, Denmark
- Part of the Civil and Architectural Engineering programme
- Positions available from 1 March 2026 or later
Research Area and Project Description
- Focus on extending the service life of civil engineering structures (e.g., bridges, buildings)
- Projects aim to develop next-generation tools for lifetime extension
- Key elements:
- Automated structural health monitoring using robotics, multi-modal data, and AI
- Cyber-physical sensing systems for training physics-informed machine learning models for loading estimation (e.g., traffic, wind)
- Candidates must submit a 2-page proposal for their preferred sub-topic, describing their contribution and a simple work plan
- Project description (½-4 pages) required, outlining ideas and research plans
Requirements
- Relevant Master’s degree in civil or mechanical engineering
- Competencies in computational methods, including:
- Computational mechanics
- Uncertainty quantification
- Machine learning
Place of Employment
- Aarhus University
- Place of work: Navitas, Inge Lehmanns Gade 10, 8000 Aarhus C, Denmark
Contacts
- Main supervisor: Associate Professor Giuseppe Abbiati ([email protected])
- For application requirements: Application guide
- Further questions: [email protected]
How to Apply
- Submit your application via this link
- Application deadline: 31 January 2026 at 23:59 CET
- Preferred starting date: 1 March 2026
Additional Information
- Only documents received before the deadline will be evaluated
- The programme committee may request further information or invite applicants to an interview
- Shortlisting will be used; only the most relevant applications will be evaluated
- Aarhus University values equality and diversity and encourages all interested candidates to apply
- Salary and terms of employment follow the applicable collective agreement
- Please mention in your application that you found the job at Jobindex
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Aarhus Universitet
Aarhus Universitet, Bygning 8001, 8002, 8003
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