ETH Zurich seeks a doctoral candidate for AI-assisted bridge assessment in special road transports. The role involves developing data-driven models to support structural evaluations, with collaboration with ASTRA and supervision by Prof. Walter Kaufmann and Dr. Sophia Kuhn.
This doctoral position focuses on enhancing bridge assessment methods for heavy road transports using AI and automation. The research will build on existing engineering practices to create efficient parametric models, supporting the Swiss Federal Roads Office (ASTRA) in evaluating over 10,000 applications annually that require structural analysis.
Responsibilities
- Conduct independent research on AI and automation applications for assessing bridge structures under heavy transport loads
- Maintain regular communication with industry partner ASTRA to ensure real-world relevance of the research
- Write a doctoral thesis and publish in peer-reviewed journals, with opportunities to present at international conferences
- Assist in teaching by co-supervising Bachelor’s and Master’s theses
- Complete 12 course credits within the doctoral programme in the relevant research field
Requirements
- Master’s degree in Civil Engineering, ideally with a focus on Structural Engineering
- Clear communication skills in English, both written and spoken, for academic and industry collaboration
- Ability to work autonomously and take initiative in research tasks
Nice to have
- Experience with scripting in Python and in AI, machine learning, or data science
- German language proficiency
What the company offers
- Supervision by Prof. Walter Kaufmann and Dr. Sophia Kuhn
- Opportunity to become an associated researcher and join the ETH AI Center community
- Access to the Center for Augmented Computational Design in Architecture, Engineering and Construction (Design++)
- Participation in career development programmes with mentors from industry and academia
- Supportive and collaborative working environment
About the company
The research group at ETH Zurich values close collaboration with industry partners such as ASTRA and fosters a supportive, collaborative environment for its members.
- Collaborative work with industry partners like ASTRA
- Supportive and team-oriented research environment
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