Doctoral Position in Risk-Based Inspection and Maintenance Planning of Tunnels

The successful candidate will map and formalise current tunnel maintenance decision processes for the structural and mechanical, electrical, and plumbing domains through workshops and interviews with practitioners. On this basis, risk and consequence models based on Bayesian networks will be formulated, and incremental risk updating methods will be developed. A computationally tractable Value of Information analysis will be developed using approximation strategies, such as surrogate models and scenario reduction. Intervention program optimisation models accounting for sequencing, bundling, access windows, and resource constraints will be formulated and solved, with outputs traceable to the underlying evidence. The candidate will contribute to validation campaigns at the Hagerbach Test Gallery and the EuroTube Foundation.

The Chair of Infrastructure Management, led by Professor Dr. Bryan T. Adey within the Institute of Construction and Infrastructure Management of the Department of Civil, Environmental and Geomatic Engineering, has an opening for a doctoral student. This position is part of an interdisciplinary SNSF project in collaboration with the Free University of Bozen-Bolzano, the Hagerbach Test Gallery, and the EuroTube Foundation.

The project Predictive, Resilient, Integrated Systems for Management of Tunnel (PRISM-T), funded by the SNSF, addresses this challenge through an integrated digital twin workflow for tunnel maintenance decision support. Heterogeneous inspection and monitoring evidence is transformed into uncertainty-aware condition indicators, which are used to update risk, to assess whether additional information is worth collecting, and to derive executable intervention programs. Extended reality (XR) is used to validate decisions and to guide inspection and maintenance work on site.

The workflow is developed and validated in the Tunnel Digitalisation Centre of the Hagerbach Test Gallery in Flums, and its transferability is tested at the DemoTube facility of the EuroTube Foundation in Dübendorf. Regular field work at both sites and close collaboration with the partner team in Bolzano form an integral part of the doctoral research.

Within this project, the doctoral position addresses the decision layer of the workflow, in which maintenance decision processes are formalised and uncertainty-aware condition indicators, developed in a companion doctoral position, are used to update risk and to optimise intervention programs under realistic tunnel constraints.

ETH Zurich is one of the world’s leading universities specialising in science and technology. We are renowned for our excellent education, cutting-edge fundamental research and direct transfer of new knowledge into society. Over 30,000 people from more than 120 countries find our university to be a place that promotes independent thinking and an environment that inspires excellence. Located in the heart of Europe, yet forging connections all over the world, we work together to develop solutions for the global challenges of today and tomorrow.

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• A Master’s degree in civil engineering, operations research, industrial engineering, applied mathematics, or a related field

• A strong background in probabilistic modelling, reliability and risk analysis, and mathematical optimisation

• Very good programming skills, preferably in Python, and experience with optimisation solvers

• Familiarity with infrastructure asset management, Bayesian networks, decision analysis, Value of Information analysis, or business process modelling would be considered an advantage

• Willingness to carry out field work in underground environments and to collaborate within an interdisciplinary and international team

• Proficiency in written and spoken English is required, and knowledge of German is regarded as an asset