PhD Position in Data- and AI-driven Transportation Infrastructure Life-Cycle Extension

PhD Position in Data- and AI-driven Transportation Infrastructure Life-Cycle Extension

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2 May yesterday Delft

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Challenge Novel AI framework for transport networks inspection and maintenance planning.Change Intelligent decision-making for real-world inspection and maintenance planning.Impact Infrastructure life-cycle extension for a future-proof built environment.

Job description

The 3D Geoinformation Group and AiDAPT Lab invite applications for a funded PhD position in the area of Data-/AI-driven infrastructure inspection and maintenance planning. We are looking for candidates highly motivated to work at the confluence of AI, geoinformation, infrastructure safety & sustainability, and algorithmic decision-making, in order to address the life-cycle extension needs of our aging and growing transportation systems.

A significant part of our transportation infrastructure, including roads and bridges, has reached or exceeded its design life. To extend the life of infrastructure in the future and at the same time meet sustainability goals, it is necessary to optimize interventions by predicting the most effective inspection and maintenance strategies, while reducing emissions, and network disruptions due to construction works or poor asset structural conditions, among others.

This PhD research will investigate how optimal inspection and maintenance strategies can be devised using geo-data, engineering models, and AI. The case study will be the city of Amsterdam, however, the methods to be developed will be generic. The PhD research will commence with an inventory of the already existing inspection and maintenance data and will first develop a method to get structured insight into degradation over time based on these historical geo-based data. In a second step, the method will be further developed to propose optimal inspection and maintenance strategies by incorporaing the various factors affecting the condition of infrastructure and its stochastic degradation over time. The method will be validated using historical evolution of road and bridge asset conditions. It will result in a probabilistic digital twin based on which we can simulate intervention actions as the third step, such as repairs, upgrades, inspections, and monitoring system installations. The effects of such interventions will be modeled as an advancement of the digital twin in a fourth step, including improvements to asset condition, delays in deterioration processes, and uncertainty in damage detection. The direction that we intend to explore is developing a novel AI pipeline for this purpose to model the effects as key performance indicators. AI models will interact with the digital twin to generate and optimize policies on when and where to inspect and perform maintenance, based on expected degradation and meeting multiple sustainability goals. For the AI pipeline, the potential for obtaining training data to establish key performance indicators from simulations will be explored, such as traffic changes, carbon emissions, and climate change risks.

The candidate's background can further motivate directions of this PhD project in coordination with supervisors and stakeholders.

The PhD candidate will combine expertise on geo-data, digital twins, and algorithmic decision-making. She/he/they will be supervised by Prof. dr. Jantien Stoter (3D Geoinformation Group) and Dr. Charalampos Andriotis (AiDAPT Lab). The candidate will work as part of a team within the groups, closely collaborating with researchers, engineers, and stakeholders associated with the City of Amsterdam and the Amsterdam Institute of Advanced Metropolitan Solutions. The research will be carried out in the context of the National Growth Fund project “Future proof living environment”. The position is funded for a duration of 4 years, during which the candidate will undertake research on their PhD topic and contribute to the research agenda of the research groups, also dependent on the interest of the candidate.


Delft University of Technology (TU Delft)


  • MSc degree (or almost completed) in computer science, geoinformatics/geomatics, engineering, or related discipline.
  • Background in at least two of the following domains: structure & infrastructure modelling, algorithmic decision-making, transportation engineering, uncertainty quantification, geo-data analytics, machine learning, and optimization.
  • Experience with data-driven and/or deep learning approaches and/or algorithmic decision-making,
  • Interest in applying AI in infrastructure networks;
  • Good programming skills in Python;
  • Familiarity with deep learning frameworks such as Pytorch and Tensorflow (preferred);
  • Excellent oral and written communication skills in English proven by a minimum score of 100 in TOEFL or IELTS of 7.0 per sub-skill (writing, reading, listening, speaking). For more details please check the Graduate Schools Admission Requirements.
  • Ability to work in a team, take initiatives, and be results-oriented.

Doing a PhD at TU Delft requires English proficiency at a certain level to ensure that the candidate is able to communicate and interact well, participate in English-taught Doctoral Education courses, and write scientific articles and a final thesis. For more details please check the Graduate Schools Admission Requirements.

Conditions of employment

Fixed-term contract: 4 years.

Doctoral candidates will be offered a 4-year period of employment in principle, but in the form of 2 employment contracts. An initial 1,5 year contract with an official go/no go progress assessment within 15 months. Followed by an additional contract for the remaining 2,5 years assuming everything goes well and performance requirements are met.

Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from € 2770 per month in the first year to € 3539 in the fourth year. As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills.

The TU Delft offers a customisable compensation package, discounts on health insurance, and a monthly work costs contribution. Flexible work schedules can be arranged.

For international applicants, TU Delft has the Coming to Delft Service. This service provides information for new international employees to help you prepare the relocation and to settle in the Netherlands. The Coming to Delft Service offers a Dual Career Programme for partners and they organise events to expand your (social) network.


Delft University of Technology

The 3D geoinformation research group focuses on the technologies underpinning geographical information systems (GIS), and aims at designing, developing, and implementing better systems to model 3D cities, buildings and landscapes. It is a multidisciplinary group of around 25 people, including computer scientists, geomatics engineers, and geographers; 6 of them are tenured staff (1 professor, 2 associate-professor, and 3 assistant-professor). It has a history of successful collaborations with the industry and the government: its research has led to open source software and standards for the management and use of 3D geo-data.

AiDAPT is TU Delft’s AI-Lab for Design, Analysis and Optimization in the Faculty of Architecture & Built Environment. The lab conducts research on decision-making under uncertainty for structural and architectural systems, at the intersection of risk & reliability, optimization, and machine learning. It is a vibrant team of engineers and computer scientists that work on novel physics-based and data-driven frameworks to understand, control, and improve built environment resilience and sustainability. As part of the TU Delft AI Initiative, AiDAPT has links with other Faculties and the ELLIS Unit.

Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context.

At TU Delft we embrace diversity as one of our core values and we actively engage to be a university where you feel at home and can flourish. We value different perspectives and qualities. We believe this makes our work more innovative, the TU Delft community more vibrant and the world more just. Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale. That is why we invite you to apply. Your application will receive fair consideration.

Challenge. Change. Impact!


Faculty Architecture & the Built Environment

The Faculty of Architecture and the Built Environment has a leading role in education and research worldwide. The driving force behind the faculty’s success is its robust research profile combined with the energy and creativity of its student body and academic community. It is buzzing with energy from early in the morning until late at night, with four thousand people studying, working, designing, conducting research and acquiring and disseminating knowledge. Our faculty has a strong focus on 'design-oriented research’, which has given it a top position in world rankings.

Staff and students are working to improve the built environment with the help of a broad set of disciplines, including architectural design, urban planning, building technology, social sciences, process management, and geo-information science. The faculty works closely with other faculties, universities, private parties, and the public sector, and has an extensive network in the Netherlands as well as internationally.

Click here to go to the website of the Faculty of Architecture and the Built


  • PhD
  • Engineering
  • max. 38 hours per week
  • €2770—€3539 per month
  • University graduate
  • TUD05332


Delft University of Technology (TU Delft)

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