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

NZZone; Zürich; Hybrid; CHF 45.000 - 55.000; Vollzeit

Zusammenfassung

ETH Zurich's Chair of Infrastructure Management invites a doctoral candidate to map and formalize tunnel maintenance decision processes for structural and MEP domains, using Bayesian networks to update risk. You will develop Value of Information analyses and intervention program optimization, employing surrogate models and scenario reduction, with validation campaigns at partner sites in Switzerland.

The project is interdisciplinary and international, offering access to digital twin workflows,

Qualifikationen

• A Master’s degree in civil engineering or related field with strong probabilistic modelling background.
• Experience in reliability and risk analysis and mathematical optimisation is essential.
• Programming skills in Python and experience with optimisation solvers are required.
• Familiarity with Bayesian networks, decision analysis and Value of Information analysis is advantageous.
• Willingness to conduct field work in underground environments and collaborate in an international team.
• Fluent written and spoken English; German is a plus.

Aufgaben

• Map and formalise tunnel maintenance decision processes across structural and MEP domains.
• Formulate risk and consequence models using Bayesian networks and update methods.
• Develop Value of Information analysis and optimization of intervention programs.
• Contribute to validation campaigns at partner facilities and in the field.

Kenntnisse

Probabilistic modelling

Reliability and risk analysis

Mathematical optimisation

Python programming

Optimization solvers

Bayesian networks

Decision analysis

Value of Information

Business process modelling

Field work readiness

English proficiency

Ausbildung

Master’s degree in civil engineering

Tools

Python

Optimization solvers

Jobbeschreibung

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 focuses risk-based inspection and maintenance planning for tunnels, including probabilistic risk updating, Value of Information analysis, and intervention program optimisation. 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 preferred starting date is 1 February 2027, although other dates are negotiable.

Project background

Tunnels are critical links in transport networks, and many Swiss road and rail tunnels are ageing while being subject to increasing traffic loads, climate-related stressors, and evolving safety requirements. Their maintenance involve two interdependent asset domains, namely structural elements, such as lining, portals, and drainage, and mechanical, electrical, and plumbing systems, such as ventilation, lighting, and fire detection. In current practice, these domains are managed largely in isolation, inspections remain heavily manual, and evidence from different campaigns, sensors, and specialists is fragmented across separate reports and databases. Interventions are therefore often planned using disjointed evidence and conservative heuristics, even where substantial data exist.

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 optimise intervention programs under realistic tunnel constraints.

Job description

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.

Profile

• 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

We offer

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.

Working, teaching and research at ETH Zurich

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In line with our values, ETH Zurich encourages an inclusive culture. We promote equality of opportunity, value diversity and nurture a working and learning environment in which the rights and dignity of all our staff and students are respected. Visit our Equal Opportunities and Diversity website to find out how we ensure a fair and open environment that allows everyone to grow and flourish. Sustainability is a core value for us – we are consistently working towards a climate-neutral future.

About ETH Zürich

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