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Aarhus Universitet

Phd - Ensuring the integrity of urban assets during underground excavations: data-driven analytical methods for design and alarm systems


Nordre Ringgade 1, 8000 Aarhus, Danmark

ID: 2347016
Indrykket for 14 dage siden
Applicants are invited for a PhD fellowship/scholarship at Graduate School of Technical Sciences, Aarhus University, Denmark, within the Civil and Architectural Engineering programme. The position is available from 01 January 2024 or later.

Ensuring the integrity of urban assets during underground excavations: data-driven analytical methods for design and alarm systems

Research area and project description
Cities drive to become carbon neutral requires the enhancement of transport infrastructure. Underground construction of new metro tunnels and circular shafts is currently over-engineered due to empiricisms in design methods. This results in unnecessary environmental and economic costs.
The project objectives are two-fold. This project will influence the revision of the Danish National Annex
First, to establish a datadriven analysis method that integrates analytical excavation-structure-interaction modelling for varying structural typologies (buildings, pipelines, tunnels) with real-world local and remote measurements. This new data-driven method can be used for preliminary design and real-time risk assessments of the next metro lines in Copenhagen or cloudburst/road tunnels. This design method will be validated against large monitoring datasets collected during the built Cityringen Metro and structural movements predicted in past design projects by Arup.

Second, to implement this analysis method in the workflow of Arup by using a probabilistic approach that can optimize the design in terms of costs and carbon footprint while quantifying the influence of incertainties. For rapid implementation, the project focuses on data analytics and modelling rather than numerical techniques with high computational costs.
  • Project description. For technical reasons, you must upload a project description. Please simply copy the project description above, and upload it as a PDF in the application.

Qualifications and specific competences
Applicants must have a relevant Master’s degree (120 ECTS). The applicant has knowledge of tunnelling, deep excavations, and induced ground movements. Preferable, the applicant has industry experience.

Place of employment and place of work
The place of employment is OVE ARUP & PARTNERS DANMARK A/S, and the place of work is Axeltorv 2K, 1609, København V.

Since it is an Industrial PhD project, the Industrial PhD candidate will be employed in the company and enrolled at Graduate School of Technical Sciences (Aarhus). The Industrial PhD candidate is expected to split the time equally between the company and the university, i.e. work equally in both places – the actual scheduling will be decided within the framework of the project.

Applicants seeking further information are invited to contact:
Assistant Professor Andrea Franza at [email protected]

How to apply
Please follow this link to submit your application.

Application deadline is 20 September 23:59 CEST.

Preferred starting date is 1 January 2024.

For information about application requirements and mandatory attachments, please see our application guide.

Please note:
  • The programme committee may request further information or invite the applicant to attend an interview.
  • Shortlisting will be used, which means that the evaluation committee only will evaluate the most relevant applications.
  • Admission is contingent upon full external funding from Innovation Fund Denmark, thus, if approved by GSTS, it will be a conditional approval until full external funding is secured.

Aarhus University’s ambition is to be an attractive and inspiring workplace for all and to foster a culture in which each individual has opportunities to thrive, achieve and develop. We view equality and diversity as assets, and we welcome all applicants. All interested candidates are encouraged to apply, regardless of their personal background.


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