PhD Position Application of Geometric Deep Learning for Real-time Urban Flooding Risk Management

PhD Position Application of Geometric Deep Learning for Real-time Urban Flooding Risk Management

Published Deadline Location
6 Jun 16 Jul Delft

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Challenge Improve sustainable water management and response to urban flooding.Change Develop cutting-edge AI solutions for urban water networks.Impact Enhance the adaptability and resilience of urban water systems by exploiting digitisation.

Job description

AidroLab is Delft Artificial Intelligence Lab (DAI-Lab) for urban water systems. As cities face growing pressure from climate change and increasing demographics, AidroLab’s mission is to develop AI solutions for sustainable water management and effective flood control. AidroLab will carry out cutting-edge fundamental and applied research in Geometric Deep Learning (GDL), exploiting digitisation to tackle water problems in the urban environment. Contrary to conventional AI techniques, GDL can effectively take the complex interrelationships of water networks and urban systems into account, allowing the development of ground-breaking data-driven solutions. The methods and tools developed by AidroLab will enhance the adaptability and resilience of urban water systems and help decision-makers and first responders to address known criticalities and uncertain future conditions.

AidroLab will employ 4 PhD students: two at the Faculty of Civil Engineering and Geosciences (CEG) and two at the Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS). While CEG students will focus on the application of AI to solve real problems related to urban water systems, EEMCS students will carry out fundamental research in GDL to provide better modelling tools. AidroLab research will be based on a strong collaboration among all the employed PhDs and research groups involved.

The following positions are open for the two PhDs of CEG Faculty:

  1. Application of Graph Neural Networks for modeling and design of adaptable urban water infrastructure.
  2. Application of Geometric Deep Learning for real-time urban flooding risk management.

Both lines of research will be carried out using simulated datasets as well as real datasets from the Netherlands and other parts of the world.

AidroLab is a Delft Artificial Intelligence Lab (DAI-Lab). Artificial intelligence, data and digitalisation are becoming increasingly important when looking for answers to major scientific and societal challenges. In a DAI-lab, experts in ‘the fundamentals of AI technology’ along with experts in ‘AI challenges’ run a shared lab. As a PhD, you will work with at least two academic members of staff and three other PhD candidates. In total, TU Delft will establish 24 DAI-Labs where 48 Tenure Trackers and 96 PhD candidates will have the opportunity to push the boundaries of science by using AI. Each team is driven by research questions which arise from scientific and societal challenges and contribute to the development and execution of domain specific education. Instead of the usual 4-year contract, you will receive a 5-year contract. Approximately a fifth of your time will be allocated to developing ground breaking learning materials and educating students in these new subjects. The experience you will gain by teaching will be invaluable for future career prospects. All team members have many opportunities for self-development. You will be a member of the thriving DAI-Lab community that fosters cross-fertilization between talents with different expertise and disciplines.

The DAI-Lab AidroLab is led by Dr. Riccardo Taormina of the Department of Water Management (CEG) and Dr. Elvin Isufi of the Department of Intelligent Systems (EEMCS).

TU Delft CEG Faculty is ranked #2 worldwide for Civil & Structural Engineering (QS2020). CEG academic members involved in AidroLab are from the Urban Water Infrastructure group led by Prof. Zoran Kapelan at the Department of Water Management, and the Hydraulic Structures and Flood Risk group led by Prof. Bas Jonkman at the Department of Hydraulic Engineering.

Dr. Taormina and Dr. Isufi will supervise the PhD students along with Prof. Z. Kapelan and Dr. J. Langeveld (Theme 1) and Prof. B. Jonkman (Theme 2).


Delft University of Technology (TU Delft)


  • Completed a relevant MSc degree in engineering or applied sciences field relevant to PhD research;
  • Demonstrated competences in one or more of these disciplines: deep learning, AI, machine learning or data science; graph theory or network science; hydraulics or fluid dynamics or other relevant fields.
  • An affinity with teaching and guiding students.
  • A passion for AI and developing AI solutions for solving engineering and societal problems in the field of water resources.
  • A proven record and interest in further developing your modelling, programming, analytical and scientific writing skills.
  • Proficiency in verbal and written English.
  • The ability to work in a team, take initiative, be results oriented, organized and creative.

Conditions of employment

Fixed-term contract: 5 years.

TU Delft offers DAI-Lab PhD-candidates a 5-year contract (as opposed to the normal 4-years), with an official go/no go progress assessment after one year. Approximately a fifth of your time will be allocated to developing ground breaking learning materials and educating students in these new subjects.
Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from € 2395 per month in the first year to € 3217 in the fifth 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 sport memberships, and a monthly work costs contribution. Flexible work schedules can be arranged. For international applicants we offer the Coming to Delft Service and Partner Career Advice to assist you with your relocation.


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. For generations, our engineers have proven to be entrepreneurial problem-solvers both in business and in a social context. TU Delft offers 16 Bachelor’s and 32 Master’s programmes to more than 23,000 students. Our scientific staff consists of 3,500 staff members and 2,800 PhD candidates. Together we imagine, invent and create solutions using technology to have a positive impact on a global scale.

Challenge. Change. Impact!


Faculty Civil Engineering & Geosciences

The Faculty of Civil Engineering & Geosciences (CEG) is committed to outstanding international research and education in the field of civil engineering, applied earth sciences, traffic and transport, water technology, and delta technology. Our research feeds into our educational programmes and covers societal challenges such as climate change, energy transition, resource depletion, urbanisation and the availability of clean water, conducted  in close cooperation with a wide range of research institutions. CEG is convinced that Open Science helps to achieve our goals and supports its scientists in integrating Open Science in their research practice. The Faculty of CEG comprises 28 research groups in the following seven departments: Materials Mechanics Management & Design, Engineering Structures, Geoscience and Engineering, Geoscience and Remote Sensing, Transport & Planning, Hydraulic Engineering and Water Management.

Click here to go to the website of the Faculty of Civil Engineering & Geosciences.


  • PhD
  • Engineering
  • 32—38 hours per week
  • University graduate
  • TUD00228


Delft University of Technology (TU Delft)

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