The Department of Engineering Systems and Services at the Delft University of Technology (TU Delft) is seeking a highly motivated and talented PhD student to join our research team.

Our infrastructure systems are increasingly threatened by crises and shocks. Disruptions caused by storms, floods, earthquakes or geopolitical conflict therefore cascade through our critical infrastructure systems, such as transportation and energy networks. The consequences of these disruptions undermine social resilience and hamper economic growth. While resilience science and policy has aimed to improve recovery within different infrastructures, there is a need to better understand and analyse how resilience propagates across systems; and how we can improve resilience throughout the transition towards a more sustainable future.

Conventionally, interdependent infrastructure resilience is evaluated by tracking overall system performance under shocks. In such methods, infrastructure resilience is often achieved by restoring functional dependencies within and among infrastructure systems that existed before the occurrence of exogeneous shocks. These models are computationally intensive and provide limited insights into actionable resilience enhancement strategies and policies that may also involve various relationships that are relevant only during crises and subsequent recovery. An alternative approach is to classify the various internal and external dependencies and model their temporal dynamics (restoration, establishment, removal, or replacement) and logical relationships during and after disaster events. In this approach, we view the recovery and adaptation capacity of infrastructure systems as the ability to dynamically alter dependencies to restore system functions.

As the successful candidate, you will contribute to analysing and better understanding of resilience of interconnected infrastructure systems. Your research will combine methodological and empirical contributions to infrastructure and urban resilience. Based on empirical research and spatial-temporal data analysis, you will conceptualize dynamic relationships that are relevant to recovery across infrastructure, and will incorporate these concepts into a computational network model to simulate different disaster impacts and recovery actions. Via scenario analysis, you will then be able to study the impact of different types of crises and disasters, and the subsequent recovery processes. In addition, this approach allows you to investigate the impact of sustainable transitions on resilience and post-disaster recovery of urban infrastructure systems. The outcome of this PhD is an improved understanding of the interdependencies of our infrastructure systems and how they respond to various shocks and transformations. This will help inform policies at different scales to improve societal resilience.

We are looking for a creative and autonomous candidate, who is keen to combine methods and approaches from different fields, such as network modelling (transport, energy, and communication networks), geospatial analysis, and agent-based modelling. This new simulation approach will be developed for one or several case studies, preferably from Netherlands with a focus on natural disasters and pandemics. However, the candidate will have the freedom to develop other case studies that can be used to demonstrate the methodology.

For modelling infrastructure networks, the candidate will integrate existing network modelling approaches or domain-specific infrastructure simulation models. The relevant dependencies that exist during different stages will be identified, classified and embedded in the infrastructure models. To reflect the demand fluctuations during shocks, the candidate will also develop empirical behavioural models and couple it with the network simulation models.

A master’s degree (or equivalent) in Infrastructure Engineering, Transportation Engineering, Systems Engineering, or a related field. (essential).

• Strong background and expertise in network analysis and simulation. Other desirable skills include agent-based modelling, and statistical modelling .
• Excellent programming skills (e.g., Python or/and Java) and familiarity with network optimization algorithms.
• Excellent working knowledge of geospatial tools, such as ArcGIS, QGIS, and geopandas.
• Experience in data collection, analysis (including statistical analysis), and visualization.
• Strong analytical and problem-solving abilities, with a keen interest in interdisciplinary research.
• Effective communication and technical writing skills in English.
• Ability to work both independently and collaboratively within a team.

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.

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

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 Technology, Policy and Management

The Faculty of TPM provides an important contribution to solving complex technical-social issues, such as energy transition, mobility, digitalisation, water management and (cyber) security. TPM does this with its excellent education and research at the intersection of technology, society and policy. We combine insights from both engineering and social sciences as well as the humanities. TPM develops robust models and designs, is internationally oriented and has an extensive network of knowledge institutions, companies, social organisations and governments.

Click here to go to the website of the Faculty of Technology, Policy and Management.