苏黎世联邦理工学院PhD position in AI-Supported Resilience Assessment申请条件要求-申请方
主办方
苏黎世联邦理工学院
PhD直招介绍
PhD Position in AI-Supported Resilience Assessment of Climate-Neutral Transport Infrastructure
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 PhD student in transport infrastructure resilience. The position is part of the EU Horizon project SHIFTIN, which aims to accelerate the transition towards climate-neutral, resilient, and biodiversity-friendly transport infrastructure by 2050.
The doctoral research will focus on developing AI-supported stress-testing and surrogate-modelling methodologies to assess the resilience of interdependent transport infrastructure systems under climate-related and multi-hazard scenarios. The work will support rapid, evidence-based evaluation of design, retrofit, maintenance, and recovery strategies at asset, corridor, and network scales.
Project background
SHIFTIN is an EU Horizon project that aims to accelerate the transition towards climate-neutral, resilient, and biodiversity-friendly transport infrastructure by 2050. Roads, railways, and ports are essential for European mobility and economic activity, but they also consume large volumes of raw materials, generate greenhouse-gas and air-pollutant emissions, fragment habitats, and are increasingly exposed to climate-related hazards such as floods, landslides, and heatwaves.
To address these challenges, SHIFTIN will demonstrate and combine circular low-carbon construction materials, nature-based solutions, advanced monitoring technologies, and digital decision-support tools. Full-scale pilots on four TEN-T corridors will cover road, rail, and port contexts, integrating infrastructure monitoring, satellite and on-board sensing, IoT-enabled structural health monitoring, and AI-supported analytics.
A Digital Twin-based Integrated Decision Support Platform will convert monitoring and modelling outputs into transparent whole-life indicators for carbon, circularity, resilience, biodiversity, and costs. These outputs will support robust business cases, maintenance planning, green public procurement, and the wider uptake of sustainable and resilient infrastructure solutions across European transport networks.
Within this broader project, the PhD research will focus on AI-supported stress-testing and surrogate modelling for transport infrastructure resilience. The goal is to enable rapid assessment of many hazard, disruption, recovery, and intervention scenarios, supporting practical decision-making for climate-resilient and sustainable transport systems.
Job description
This doctorate aims to advance the state of the art in simulation-informed, AI-supported resilience assessment for transport infrastructure. Working closely with academic, industry, infrastructure, and public-sector partners across Europe, the candidate will contribute to the development of stress-testing frameworks, surrogate modelling algorithms, and decision-support tools for climate-resilient and sustainable transport systems. The candidate’s core tasks will include:
Developing AI-supported surrogate models for infrastructure stress testing
Linking surrogate models with agent-based and network-based simulations
Assessing infrastructure interdependencies and recovery constraints
Supporting resilience assessment across asset, corridor, and network scales
Contributing to cost-benefit and decision-support analysis
Addressing uncertainty, reliability, and explainability
Integrating results with digital-twin and monitoring data
Collaborating with the European project consortium
Working, teaching and research at ETH Zurich
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We value diversity and sustainability
In line with our values( https://ethz.ch/en/the-eth-zurich.html ), 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( https://ethz.ch/staffnet/en/employment-and-work/working-environment/diversity.html ) 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( https://ethz.ch/en/the-eth-zurich/sustainability.html ).
About ETH Zürich
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苏黎世联邦理工学院 PhD position in AI-Supported Resilience Assessment项目有没有奖学金，是不是全奖Phd招生，下面我们一起看一下【大学名称】Phd的奖学金资助情况
项目资助情况
We offer
Your job with impact: Become part of ETH Zurich, which not only supports your professional development, but also actively contributes to positive change in society
You can expect numerous benefits( https://ethz.ch/staffnet/en/employment-and-work/employment/offers-and-benefits.html ), such as public transport season tickets and car sharing, a wide range of sports offered by the ASVZ( https://asvz.ch/en/634-welcome-asvz ), childcare( https://ethz.ch/en/the-eth-zurich/working-teaching-and-research/working-environment/family/childcare.html ) and attractive pension benefits( https://www.publica.ch/en/about-us/pension-plans/eth-domain-pension-plan )
苏黎世联邦理工学院Phd申请条件和要求都有哪些？PhD position in AI-Supported Resilience Assessment项目是不是全奖？有没有奖学金？下面我们一起看一下苏黎世联邦理工学院申请Phd直招需要具备哪些条件和要求，以及托福、雅思语言成绩要到多少才能申请。
申请要求
Profile
A Master’s degree in civil engineering, transport engineering, infrastructure systems, environmental engineering, computational engineering, data science, or a closely related field
Strong quantitative and programming skills, preferably in Python, with experience in machine learning, statistical modelling, simulation, optimisation, data analysis, or geospatial/network analysis
Excellent written and spoken English skills
Knowledge of German or another European language is an asset but not required
报名方式
申请链接
招生人信息
Ms. Nathalie Dietrich
邮箱：dietrich@ibi.baug.ethz.ch
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